By Jacqi Levy

The Internet of Things (IoT) is transforming every facet of the building – how we inhabit them, how we manage them, and even how we build them. There is a vast ecosystem around today’s buildings, and no part of the ecosystem is untouched.

In this blog series, I plan to examine the trends being driven by IoT across the buildings ecosystem. Since the lifecycle of building begins with design and construction, let’s start there. Here are four ways that the IoT is radically transforming building design and construction.

Building information modeling

Building information modeling (BIM) is a process that provides an intelligent, 3D model of a building. Typically, BIM is used to model a building’s structure and systems during design and construction, so that changes to one set of plans can be updated simultaneously in all other impacted plans. Taken a step further, however, BIM can also become a catalyst for smart buildings projects.

Once a building is up and running, data from IoT sensors can be pulled into the BIM. You can use that data to model things like energy usage patterns, temperature trends or people movement throughout a building. The output from these models can then be analyzed to improve future buildings projects. Beyond its impact on design and construction, BIM also has important implications for the management of building operations.

Green building

The construction industry is a huge driver of landfill waste – up to 40% of all solid waste in the US comes from the buildings projects. This unfortunate fact has ignited a wave of interest in sustainable architecture and construction. But the green building movement has become about much more than keeping building materials out of landfills. It is influencing the design and engineering of building systems themselves, allowing buildings to reduce their impact on the environment through energy management.

Today’s green buildings are being engineered to do things like shut down unnecessary systems automatically when the building is unoccupied, or open and close louvers automatically to let in optimal levels of natural light. In a previous post, I talk about 3 examples of the IoT in green buildings, but these are just some of the cool ways that the construction industry is learning to be more sustainable with help from the IoT.

Intelligent prefab

Using prefabricated building components can be faster and more cost effective than traditional building methods, and it has an added benefit of creating less construction waste. However, using prefab for large commercial buildings projects can be very complex to coordinate. The IoT is helping to solve this problem.

Using RFID sensors, individual prefab parts can be tracked throughout the supply chain. A recent example is the construction of the Leadenhall Building in London. Since the building occupies a relatively small footprint but required large prefabricated components, it was a logistically complex task to coordinate the installation. RFID data was used to help mitigate the effects of any downstream delays in construction. In addition, the data was the fed into the BIM once parts were installed, allowing for real time rendering of the building in progress, as well as establishment of project controls and KPIs.

Construction management

Time is money, so any delays on a construction project can be costly. So how do you prevent your critical heavy equipment from going down and backing up all the other trades on site? With the IoT!

Heavy construction equipment is being outfitted with sensors, which can be remotely monitored for key indicators of potential maintenance issues like temperature fluctuations, excessive vibrations, etc. When abnormal patterns are detected, alerts can trigger maintenance workers to intervene early, before critical equipment fails. Performing predictive maintenance in this way can save time and money, as well as prevent unnecessary delays in construction projects.

Originally posted here.

By Ashley Ferguson

Thanks to the introduction of connected products, digital services, and increased customer expectations, it has been the trend for IoT enterprise spend to consistently increase. The global IoT market is projected to reach $1.4 trillion USD by 2027. The pressure to build IoT solutions and get a return on those investments has teams on a frantic search for IoT engineers to secure in-house IoT expertise. However, due to the complexity of IoT solutions, finding this in a single engineer is a difficult or impossible proposition.

So how do you adjust your search for an IoT engineer? The first step is to acknowledge that IoT solution development requires the fusion of multiple disciplines. Even simple IoT applications require hardware and software engineering, knowledge of protocols and connectivity, web development skills, and analytics. Certainly, there are many engineers with IoT knowledge, but complete IoT solutions require a team of partners with diverse skills. This often requires utilizing external sources to supplement the expertise gaps.

THE ANATOMY OF AN IoT SOLUTION

IoT solutions provide enterprises with opportunities for innovation through new product offerings and cost savings through refined operations. An IoT solution is an integrated bundle of technologies that help users answer a question or solve a specific problem by receiving data from devices connected to the internet. One of the most common IoT use cases is asset tracking solutions for enterprises who want to monitor trucks, equipment, inventory, or other items with IoT. The anatomy of an asset tracking IoT solution includes the following:

This is a simple asset tracking example. For more complex solutions including remote monitoring or predictive maintenance, enterprises must also consider installation, increased bandwidth, post-development support, and UX/UI for the design of the interface for customers or others who will use the solution. Enterprise IoT solutions require an ecosystem of partners, components, and tools to be brought to market successfully.

Consider the design of your desired connected solution. Do you know where you will need to augment skills and services?

If you are in the early stages of IoT concept development and at the center of a buy vs. build debate, it may be a worthwhile exercise to assess your existing team’s skills and how they correspond with the IoT solution you are trying to build.

IoT SKILLS ASSESSMENT

• Hardware
• Firmware
• Connectivity
• Programming
• Cloud
• Data Science
• Presentation
• Technical Support and Maintenance
• Security
• Organizational Alignment

MAKING TIME FOR IoT APPLICATION DEVELOPMENT

The time it will take your organization to build a solution is dependent on the complexity of the application. One way to estimate the time and cost of IoT application development is with Indeema’s IoT Cost Calculator. This tool can help roughly estimate the hours required and the cost associated with the IoT solution your team is interested in building. In MachNation’s independent comparison of the Losant Enterprise IoT Platform and Azure, it was determined that developers could build an IoT solution in 30 hours using Losant and in 74-94 hours using Microsoft Azure.

As you consider IoT application development, consider the makeup of your team. Is your team prepared to dedicate hours to the development of a new solution, or will it be a side project? Enterprise IT teams are often in place to maintain existing operating systems and to ensure networks are running smoothly. In the event that an IT team is tapped to even partially build an IoT solution, there is a great chance that the IT team will need to invite partners to build or provide part of the stack.

HOW THE IoT JOB GETS DONE

Successful enterprises recognize early on that some of these skills will need to be augmented through additional people, through an ecosystem, or with software. It will require more than one ‘IoT engineer’ for the job. According to the results of a McKinsey survey, “the preferences of IoT leaders suggest a greater willingness to draw capabilities from an ecosystem of technology partners, rather than rely on homegrown capabilities.”

IoT architecture alone is intricate. Losant, an IoT application enablement platform, is designed with many of the IoT-specific components already in place. Losant enables users to build applications in a low-to-no code environment and scale them up to millions of devices. Losant is one piece in the wider scope of an IoT solution. In order to build a complete solution, an enterprise needs hardware, software, connectivity, and integration. For those components, our team relies on additional partners from the IoT ecosystem.

The IoT ecosystem, also known as the IoT landscape, refers to the network of IoT suppliers (hardware, devices, software platforms, sensors, connectivity, software, systems integrators, data scientists, data analytics) whose combined services help enterprises create complete IoT solutions. At Losant, we’ve built an IoT ecosystem with reliable experienced partners. When IoT customers need custom hardware, connectivity, system integrators, dev shops, or other experts with proven IoT expertise, we can tap one of our partners to help in their areas of expertise.

SECURE, SCALABLE, SEAMLESS IoT

Creating secure, scalable, and seamless IoT solutions for your environment begins by starting small. Starting small gives your enterprise the ability to establish its ecosystem. Teams can begin with a small investment and apply learnings to subsequent projects. Many IoT success stories begin with enterprises setting out to solve one problem. The simple beginnings have enabled them to now reap the benefits of the data harvest in their environments.

Originally posted here.

By Tony Pisani

For midstream oil and gas operators, data flow can be as important as product flow. The operator’s job is to safely move oil and natural gas from its extraction point (upstream), to where it’s converted to fuels (midstream), to customer delivery locations (downstream). During this process, pump stations, meter stations, storage sites, interconnection points, and block valves generate a substantial volume and variety of data that can lead to increased efficiency and safety.

“Just one pipeline pump station might have 6 Programmable Logic Controllers (PLCs), 12 flow computers, and 30 field instruments, and each one is a source of valuable operational information,” said Mike Walden, IT and SCADA Director for New Frontier Technologies, a Cisco IoT Design-In Partner that implements OT and IT systems for industrial applications. Until recently, data collection from pipelines was so expensive that most operators only collected the bare minimum data required to comply with industry regulations. That data included pump discharge pressure, for instance, but not pump bearing temperature, which helps predict future equipment failures.

A turnkey solution to modernize midstream operations

Now midstream operators are modernizing their pipelines with Industrial Internet of Things (IIoT) solutions. Cisco and New Frontier Technologies have teamed up to offer a solution combining the Cisco 1100 Series Industrial Integrated Services Router, Cisco Edge Intelligence, and New Frontier’s know-how. Deployed at edge locations like pump stations, the solution extracts data from pipeline equipment and is sent via legacy protocols, transforming data at the edge to a format that analytics and other enterprise applications understand. The transformation also minimizes bandwidth usage.

Mike Walden views the Cisco IR1101 as a game-changer for midstream operators. He shared with me that “Before the Cisco IR1101, our customers needed four separate devices to transmit edge data to a cloud server—a router at the pump station, an edge device to do protocol conversion from the old to the new, a network switch, and maybe a firewall to encrypt messages…With the Cisco IR1101, we can meet all of those requirements with one physical device.”

Collect more data, at almost no extra cost

Using this IIoT solution, midstream operators can for the first time:

• Collect all available field data instead of just the data on a polling list. If the maintenance team requests a new type of data, the operations team can meet the request using the built-in protocol translators in Edge Intelligence. “Collecting a new type of data takes almost no extra work,” Mike said. “It makes the operations team look like heroes.”
• Collect data more frequently, helping to spot anomalies. Recording pump discharge pressure more frequently, for example, makes it easier to detect leaks. Interest in predicting (rather than responding to) equipment failure is also growing. The life of pump seals, for example, depends on both the pressure that seals experience over their lifetime and the peak pressures. “If you only collect pump pressure every 30 minutes, you probably missed the spike,” Mike explained. “If you do see the spike and replace the seal before it fails, you can prevent a very costly unexpected outage – saving far more than the cost of a new seal.”
• Protect sensitive data with end-to-end security. Security is built into the IR1101, with secure boot, VPN, certificate-based authentication, and TLS encryption.
• Give IT and OT their own interfaces so they don’t have to rely on the other team. The IT team has an interface to set up network templates to make sure device configuration is secure and consistent. Field engineers have their own interface to extract, transform, and deliver industrial data from Modbus, OPC-UA, EIP/CIP, or MQTT devices.

As Mike summed it up, “It’s finally simple to deploy a secure industrial network that makes all field data available to enterprise applications—in less time and using less bandwidth.”

Originally posted here.

By GE Digital

“The End of Cloud Computing.” “The Edge Will Eat The cloud.” “Edge Computing—The End of Cloud Computing as We Know It.”  

Such headlines grab attention, but don’t necessarily reflect reality—especially in Industrial Internet of Things (IoT) deployments. To be sure, edge computing is rapidly emerging as a powerful force in turning industrial machines into intelligent machines, but to paraphrase Mark Twain: “The reports of the death of cloud are greatly exaggerated.” 

The Tipping Point: Edge Computing Hits Mainstream

We’ve all heard the stats—billions and billions of IoT devices, generating inconceivable amounts of big data volumes, with trillions and trillions of U.S. dollars to be invested in IoT over the next several years. Why? Because industrials have squeezed every ounce of productivity and efficiency out of operations over the past couple of decades, and are now looking to digital strategies to improve production, performance, and profit. 

The Industrial Internet of Things (IIoT) represents a world where human intelligence and machine intelligence—what GE Digital calls minds and machines—connect to deliver new value for industrial companies. 

In this new landscape, organizations use data, advanced analytics, and machine learning to drive digital industrial transformation. This can lead to reduced maintenance costs, improved asset utilization, and new business model innovations that further monetize industrial machines and the data they create. 

Despite the “cloud is dead” headlines, GE believes the cloud is still very important in delivering on the promise of IIoT, powering compute-intense workloads to manage massive amounts of data generated by machines. However, there’s no question that edge computing is quickly becoming a critical factor in the total IIoT equation.

Computer vision is fundamental to capturing real-world data within the IoT. Arm technology provides a secure ecosystem for smart cameras in business, industrial and home applications

By Mohamed Awad, VP IoT & Embedded, Arm

Computer vision leverages artificial intelligence (AI) to enable devices such as smart cameras to interpret and understand what is happening in an image. Recreating a sensor as powerful as the human eye with technology opens up a wide and varied range of use cases for computers to perform tasks that previously required human sight – so it’s no wonder that computer vision is quickly becoming one of the most important ways to capture and act on real-world data within the Internet of Things (IoT).

Smart cameras now use computer vision in a range of business and industrial applications, from counting cars in parking lots to monitoring footfall in retail stores or spotting defects on a production line. And in the home, smart cameras can tell us when a package has been delivered, whether the dog escaped from the back yard or when our baby is awake.

Across the business and consumer worlds, the adoption of smart camera technology is growing exponentially. In its 2020 report “Cameras and Computing for Surveillance and Security”, market research and strategy consulting company Yole Développement estimates that for surveillance alone, there are approximately one billion cameras across the world. That number of installations is expected to double by 2024.

This technology features key advancements in security, heterogeneous computing, image processing and cloud services – enabling future computer vision products that are more capable than ever.

Smart camera security is top priority for computer vision

IoT security is a key priority and challenge for the technology industry. It’s important that all IoT devices are secure from exploitation by malicious actors, but it’s even more critical when that device captures and stores image data about people, places and high-value assets.

Unauthorized access to smart cameras tasked with watching over factories, hospitals, schools or homes would not only be a significant breach of privacy, it could also lead to untold harm—from plotting crimes to the leaking of confidential information. Compromising a smart camera could also provide a gateway, giving a malicious actor access to other devices within the network – from door, heating and lighting controls to control over an entire smart factory floor.

We need to be able to trust smart cameras to maintain security for us all, not open up new avenues for exploitation. Arm has embraced the importance of security in IoT devices for many years through its product portfolio offerings such as Arm TrustZone for both Cortex-A and Cortex-M.

In the future, smart camera chips based on the Armv9 architecture will add further security enhancements for computer vision products through the Arm Confidential Compute Architecture (CCA).

Further to this, Arm promotes common standards of security best practice such as PSA Certified and PARSEC. These are designed to ensure that all future smart camera deployments have built-in security, from the point the image sensor first records the scene to storage, whether that data is stored locally or in the cloud by using advanced security and data encryption techniques.

Endpoint AI powers computer vision in smart camera devices

The combination of image sensor technology and endpoint AI is enabling smart cameras to infer increasingly complex insights from the vast amounts of computer vision data they capture. New machine learning capabilities within smart camera devices meet a diverse range of use cases – such as detecting individual people or animals, recognizing specific objects and reading license plates. All of these applications for computer vision require ML algorithms running on the endpoint device itself, rather than sending data to the cloud for inference. It’s all about moving compute closer to data.

For example, a smart camera employed at a busy intersection could use computer vision to determine the number and type of vehicles waiting at a red signal at various hours throughout the day. By processing its own data and inferring meaning using ML, the smart camera could automatically adjust its timings in order to reduce congestion and limit build-up of emissions automatically without human involvement.

Arm’s investment in AI for applications in endpoints and beyond is demonstrated through its range of Ethos machine learning processors: highly scalable and efficient NPUs capable of supporting a range of 0.1 to 10 TOP/s through many-core technologies. Software also plays a vital role in ML and this is why Arm continues to support the open-source community through the Arm NN SDK and TensorFlow Lite for Microcontrollers (TFLM) open-source frameworks.

These machine learning workload frameworks are based on existing neural networks and power-efficient Arm Cortex-A CPUs, Mali GPUs and Ethos NPUs as well as Arm Compute library and CMSIS-NN – a collection of low-level machine learning functions optimized for Cortex-A CPU, Cortex-M CPU and Mali GPU architectures.

The Armv9 architecture supports enhanced AI capabilities, too, by providing accessible vector arithmetic (individual arrays of data that can be computed in parallel) via Scalable Vector Extension 2 (SVE2). This enables scaling of the hardware vector length without having to rewrite or recompile code. In the future, extensions for matrix multiplication (a key element in enhancing ML) will push the AI envelope further.

Smart cameras connected in the cloud

Cloud and edge computing is also helping to expedite the adoption of smart cameras. Traditional CCTV architectures saw camera data stored on-premises via a Network Video Recorder (NVR) or a Digital Video Recorder (DVR). This model had numerous limitations, from the vast amount of storage required to the limited number of physical connections on each NVR.

Moving to a cloud-native model simplifies the rollout of smart cameras enormously: any number of cameras can be provisioned and managed via a configuration file downloaded to the device. There’s also a virtuous cycle at play: Data from smart cameras can be now used to train the models in the cloud for specific use-cases so that cameras become even smarter. And the smarter they become, the less data they need to send upstream.

The use of cloud computing also enables automation of processes via AI sensor fusion by combining computer vision data from multiple smart cameras. Taking our earlier example of the smart camera placed at a road intersection, cloud AI algorithms could combine data from multiple cameras to constantly adjust traffic light timings holistically across an entire city, keeping traffic moving.

Arm enables the required processing continuum from cloud to endpoint. Cortex-M microcontrollers and Cortex-A processors power smart cameras, with Cortex-A processors also powering edge gateways. Cloud and edge servers harness the capabilities of the Neoverse platform.

New hardware and software demands on smart cameras

The compute needs for computer vision devices continue to grow year over year, with ultra-high resolution video capture (8K 60fps) and 64-bit (Armv8-A) processing marking the current standard for high-end smart camera products.

As a result, the system-on-chip (SoC) within next-generation smart cameras will need to embrace heterogenous architectures, combining CPUs, GPUs, NPUs alongside dedicated hardware for functions like computer vision, image processing, video encoding and decoding.

Storage, too, is a key concern: While endpoint AI can reduce storage requirements by processing images locally on the camera, many use cases will require that data be retained somewhere for safety and security – whether on the device, in edge servers or in the cloud.

To ensure proper storage of high-resolution computer vision data, new video encoding and decoding standards such as H.265 and AV1 are becoming the de facto standard.

New use cases driving continuous innovation

Overall, the demands from the new use cases are driving the need for continuous improvement in computing and imaging technologies across the board.

When we think about image-capturing devices such as CCTV cameras today, we should no longer imagine grainy images of barely recognizable faces passing by a camera. Advancements in computer vision – more efficient and powerful compute coupled with the intelligence of AI and machine learning – are making smart cameras not just image sensors but image interpreters. This bridge between the analog and digital worlds is opening up new classes of applications and use cases that were unimaginable a few years ago.

Originally posted here.

TinyML focuses on optimizing machine learning (ML) workloads so that they can be processed on microcontrollers no bigger than a grain of rice and consuming only milliwatts of power.

Once again, I’m jumping up and down in excitement because I’m going to be hosting a panel discussion as part of a webinar series — Fast and Fearless: The Future of IoT Software Development — being held under the august auspices of IotCentral.io

At this event, the second of a four-part series, we will be focusing on “AI and IoT Innovation” (see also What the FAQ are AI, ANNs, ML, DL, and DNNs? and What the FAQ are the IoT, IIoT, IoHT, and AIoT?).

Panel members Karl Fezer (upper left), Wei Xiao (upper right), Nikhil Bhaskaran (lower left), and Tina Shyuan (bottom right) (Click image to see a larger version)

As we all know, the IoT is transforming the software landscape. What used to be a relatively straightforward embedded software stack has been revolutionized by the IoT, with developers now having to juggle specialized workloads, security, artificial intelligence (AI) and machine learning (ML), real-time connectivity, managing devices that have been deployed into the field… the list goes on.

In this webinar — which will be held on Tuesday 29 June 2021 from 10:00 a.m. to 11:00 a.m. CDT — I will be joined by four industry luminaries to discuss how to juggle the additional complexities that machine learning adds to IoT development, why on-device machine learning is more important now than ever, and what the combination of AI and IoT looks like for developers in the future.

The luminaries in question (and whom I will be questioning) are Karl Fezer (AI Ecosystem Evangelist at Arm), Wei Xiao (Principal Engineer, Sr. Strategic Alliances Manager at Nvidia), Nikhil Bhaskaran (Founder of Shunya OS), and Tina Shyuan (Director of Product Marketing at Qeexo).

So, what say you? Dare I hope that we will have the pleasure of your company and that you will be able to join us to (a) tease your auditory input systems with our discussions and (b) join our question-and-answer free-for-all frensy at the end? If so, may I suggest that you Register Now before all of the good virtual seats are taken, metaphorically speaking, of course.

>> Clicke here to register

by Gus Vos

Unless you have been living under a rock, you have been seeing and hearing a lot about&nbsp5G these days. In addition, if you are at all involved in Internet of Things (IoT) or other initiatives at your organization that use cellular networking technologies, you have also likely heard about 5G New Radio, otherwise known as 5G NR, the new 5G radio access technology specification.

However, all the jargon, hype, and sometimes contradictory statements made by solution providers, the media, and analysts regarding 5G and 5G NR can make it difficult to understand what 5G NR actually is, how it works, what its advantages are, to what extent it is different than other cellular radio access technologies, and perhaps most importantly, how your organization can use this new radio access technology.

In this blog, we will provide you with an overview on 5G NR, offering you answers to these and other basic 5G NR questions – with a particular focus on what these answers mean for those in the IoT industry. 

We can’t promise to make you a 5G NR expert with this blog – but we can say that if you are confused about 5G NR before reading it, you will come away afterward with a better understanding of what 5G NR is, how it works, and how it might transform your industry.

What is the NR in 5G NR?

As its name implies, 5G New Radio or 5G NR is the new radio access technology specification found in the 5G standard. 

Set by the 3rd Generation Partnership Project (3GPP) telecommunications standards group, the 5G NR specification defines how 5G NR edge devices (smart phones, embedded modules, routers, and gateways) and 5G NR network infrastructure (base stations, small cells, and other Radio Access Network equipment) wirelessly transmit data. To put it another way, 5G NR describes how 5G NR edge devices and 5G NR network infrastructure use radio waves to talk to each other. 

5G NR is a very important part of 5G. After all, it describes how 5G solutions will use radio waves to wirelessly transmit data faster and with less latency than previous radio access technology specifications. However, while 5G NR is a very important part of the new 5G standard, it does not encompass everything related to 5G. 

For example, 5G includes a new core network architecture standard (appropriately named 5G Core Network or 5GCN) that specifies the architecture of the network that collects, processes, and routes data from edge devices and then sends this data to the cloud, other edge devices, or elsewhere. The 5GCN will improve 5G networks’ operational capacity, efficiency, and performance.

However, 5GCN is not a radio access technology like 5G NR, but rather a core network technology. In fact, networks using the 5GCN core network will be able to work with previous types of radio access technologies – like LTE. 

Is 5G NR one of 5G’s most important new technological advancements? Yes. But it is not the only technological advancement to be introduced by 5G.  

How does 5G NR work?

Like all radio access communications technology specifications, the 5G NR specification describes how edge devices and network infrastructure transmit data to each other using electromagnetic radio waves. Depending on the frequency of the electromagnetic waves (how long the wave is), it occupies a different part of the wireless spectrum.

Some of the waves that 5G NR uses have frequencies of between 400 MHz and 6 GHz. These waves occupy what is called sub-6 spectrum (since their frequencies are all under 6 GHz).

This sub-6 spectrum is used by other cellular radio access technologies, like LTE, as well. In the past, using different cellular radio access technologies like this over the same spectrum would lead to unmanageable interference problems, with the different technologies radio waves interfering with each other. 

One of 5G NR’s many advantages is that it’s solved this problem, using a technology called Dynamic Spectrum Sharing (DSS). This DSS technology allows 5G NR signals to use the same band of spectrum as LTE and other cellular technologies, like LTE-M and NB-IoT. This allows 5G NR networks to be rolled out without shutting down LTE or other networks that support existing LTE smart phones or IoT devices. You can learn more about DSS, and how it speeds the rollout of 5G NR while also extending the life of IoT devices, here.

One of 5G NR’s other major advancements is that it does not just use waves in the sub-6 spectrum to transmit data. The 5G NR specification also specifies how edge devices and network infrastructure can use radio waves in bands between 24 GHz and 52 GHz to transmit data.

These millimeter wave (mmWave) bands greatly expand the amount of spectrum available for wireless data communications. The lack of spectrum capacity has been a problem in the past, as there is a limited number of bands of sub-6 spectrum available for organizations to use for cellular communications, and many of these bands are small. Lack of available capacity and narrow spectrum bands led to network congestion, which limits the amount of data that can be transmitted over networks that use sub-6 spectrum. 

mmWave opens up a massive amount of new wireless spectrum, as well as much broader bands of wireless spectrum for cellular data transmission. This additional spectrum and these broader spectrum bands increase the capacity (amount of data) that can be transmitted over these bands, enabling 5G NR mmWave devices to achieve data speeds that are four or more times faster than devices that use just sub-6 spectrum. 

The additional wireless capacity provided by mmWave also reduces latency (the time between when device sends a signal and when it receives a response). By reducing latency from 10 milliseconds with sub-6 devices to 3-4 milliseconds or lower with 5G NR mmWave devices, 5G enables new industrial automation, autonomous vehicle and immersive gaming use cases, as well as Virtual Reality (VR), Augmented Reality (AR), and similar Extended Reality (XR) use cases, all of which require very low latency. 

On the other hand, these new mmWave devices and network infrastructure come with new technical requirements, as well as drawbacks associated with their use of mmWave spectrum. For example, mmWave devices use more power and generate more heat than sub-6 devices. In addition, mmWave signals have less range and do not penetrate walls and other physical objects as easily as sub-6 waves. 5G NR includes some technologies, such as beamforming and massive Multiple Input Multiple Output (MIMO) that lessen some of these range and obstacle penetration limitations – but they do not eliminate them. 

To learn more about the implications of 5G NR mmWave on the design of IoT and other products, read our blog, Seven Tips For Designing 5G NR mmWave Products.

In addition, there has been a lot written on these two different “flavors” (sub-6 and mmWave) of 5G NR. If you are interested in learning more about the differences between sub-6 5G NR and mmWave 5G NR, and how together they enable both evolutionary and revolutionary changes for Fixed Wireless Access (FWA), mobile broadband, IoT and other wireless applications, read our previous blog A Closer Look at the Five Waves of 5G.

What is the difference between 5G NR and LTE?

Though sub-6 and mmWave are very different, both types of 5G NR provide data transfer speed, latency, and other performance improvements compared to LTE, the previous radio access technology specification used for cellular communications. 

For example, outside of its use of mmWave, 5G NR features other technical advancements designed to improve network performance, including:

• Flexible numerology, which enables 5G NR network infrastructure to set the spacing between subcarriers in a band of wireless spectrum at 15, 30, 60, 120 and 240 kHz, rather than only use 15 kHz spacing, like LTE. This flexible numerology is what allows 5G NR to use mmWave spectrum in the first place. It also improves the performance of 5G NR devices that use higher sub-6 spectrum, such as 3.5 GHz C-Band spectrum, since the network can adjust the subcarrier spacing to meet the particular spectrum and use case requirements of the data it is transmitting. For example, when low latency is required, the network can use wider subcarrier spacing to help improve the latency of the transmission.
• Beamforming, in which massive MIMO (multiple-input and multiple-output) antenna technologies are used to focus wireless signal and then sweep them across areas till they make a strong connection. Beamforming helps extend the range of networks that use mmWave and higher sub-6 spectrum.  
• Selective Hybrid Automatic Repeat Request (HARQ), which allows 5G NR to break large data blocks into smaller blocks, so that when there is an error, the retransmission is smaller and results in higher data transfer speeds than LTE, which transfers data in larger blocks. 
• Faster Time Division Duplexing (TDD), which enables 5G NR networks to switch between uplink and downlink faster, reducing latency. 
• Pre-emptive scheduling, which lowers latency by allowing higher-priority data to overwrite or pre-empt lower-priority data, even if the lower-priority data is already being transmitted. 
• Shorter scheduling units that trim the minimum scheduling unit to just two symbols, improving latency.
• A new inactive state for devices. LTE devices had two states – idle and connected. 5G NR includes a new state – inactive – that reduces the time needed for an edge device to move in and out of its connected state (the state used for transmission), making the device more responsive. 

These and the other technical advancements made to 5G NR are complicated, but the result of these advancements is pretty simple – faster data speeds, lower latency, more spectrum agility, and otherwise better performance than LTE. 

Are LPWA radio access technology specifications, like NB-IoT and LTE-M, supported by 5G?

Though 5G features a new radio access technology, 5G NR, 5G supports other radio access technologies as well. This includes the Low Power Wide Area (LPWA) technologies, Narrowband IoT (NB-IoT), and Long Term Evolution for Machines (LTE-M). In fact, these LPWA standards are the standards that 5G uses to address one of its three main use cases – Massive, Machine-Type Communications (mMTC). 

Improvements have been and continue to be made to these 5G LPWA standards to address these mMTC use cases – improvements that further lower the cost of LPWA devices, reduce these devices’ power usage, and enable an even larger number of LPWA devices to connect to the network in a given area.

What are the use cases for 5G NR and 5G LPWA Radio Access Technologies?

Today, LTE supports three basic use cases:

• Voice: People today can use LTE to talk to each other using mobile devices. 
• Mobile broadband (MBB): People can use smartphones, tablets, mobile and other edge devices to view videos, play games, and use other applications that require broadband data speeds.
• IoT: People can use cellular modules, routers, and other gateways embedded in practically anything – a smart speaker, a dog collar, a commercial washing machine, a safety shoe, an industrial air purifier, a liquid fertilizer storage tank – to transmit data from the thing to the cloud or a private data center and back via the internet.  

5G NR, as well as 5G’s LPWA radio access technologies (NB-IoT and LTE-M) will continue to support these existing IoT and voice use cases. 

However, 5G also expands on the MBB use case with a new Enhanced Mobile Broadband (eMBB) use case. These eMBB use cases leverage 5G NR’s higher peak and average speeds and lower latency to enable smart phones and other devices to support high-definition cloud-based immersive video games, high quality video calls and new VR, AR, and other XR applications.

In addition, 5G NR also supports a new use case, called Ultra-Reliable, Low-Latency Communications (URLLC). 5G NR enables devices to create connections that are ultra-reliable with very low latency. With these new 5G NR capabilities, as well as 5G NR’s support for very fast handoffs and high mobility, organizations can now deploy new factory automation, smart city 2.0 and other next generation Industrial IoT (IIoT) applications, as well as Vehicle-to-everything (V2X) applications, such as autonomous vehicles. 

As we mentioned above, 5G will also support the new mMTC use case, which represents an enhancement of the existing IoT use case. However, in the case of mMTC, new use cases will be enabled by improvements to LTE-M and NB-IoT radio access technology standards, not 5G NR. Examples of these types of new mMTC use cases include large-scale deployments of small, low cost edge devices (like sensors) for smart city, smart logistics, smart grid, and similar applications.

But this is not all. 3GPP is looking at additional new use cases (and new technologies for these use cases), as discussed in this recent blog on Release 17 of the 5G standard. One of these new technologies is a new Reduced Capability (RedCap) device – sometimes referred to as NR Light – for IoT or MTC use cases that require faster data speeds than LPWA devices can provide, but also need devices that are less expensive than the 5G NR devices being deployed today.

3GPP is also examining standard changes to NR, LTE-M, and NB-IoT in 5G Release 17 that would make it possible for satellites to use these technologies for Non-Terrestrial Network (NTN) communications. This new NTN feature would help enable the deployment of satellites able to provide NR, LTE-M, and NB-IoT coverage in very remote areas, far away from cellular base stations.

What should you look for in a 5G NR module, router or gateway solution?

While all 5G NR edge devices use the 5G NR technology specification, they are not all created equal. In fact, the flexibility, performance, quality, security, and other capabilities of a 5G NR edge device can make the difference between a successful 5G NR application rollout and a failed one. 

As they evaluate 5G NR edge devices for their application, organizations should ask themselves the following questions:

• Is the edge device multi-mode? 
While Mobile Network Operators (MNOs) are rapidly expanding their 5G NR networks, there are still many areas where 5G NR coverage is not available. Multi-mode edge devices that can support LTE, or even 3G, help ensure that wherever the edge device is deployed, it will be able to connect to a MNO’s network – even if this connection does not provide the data speed, latency, or other performance needed to maximize the value of the 5G NR application. 

In addition, many MNOs are rolling out non-standalone (NSA) 5G NR networks at first. These NSA 5G NR networks need a LTE connection in addition to a 5G NR connection to transmit data from and to 5G NR devices. If your edge device does not include support for LTE, it will not be able to use 5G NR on these NSA networks. 

• How secure are the edge devices? 
Data is valuable and sensitive – and the data transmitted by 5G NR devices is no different. To limit the risk that this data is exposed, altered, or destroyed, organizations need to adopt a Defense in Depth approach to 5G NR cybersecurity, with layers of security implemented at the cloud, network, and edge device levels. 

At the edge device level, organizations should ensure their devices have security built-in with features such as HTTPS, secure socket, secure boot, and free unlimited firmware over-the-air (FOTA) updates. 

Organizations will also want to use edge devices from trustworthy companies that are headquartered in countries that have strict laws in place to protect customer data. In doing so you will ensure these companies are committed to working with you to prevent state or other malicious actors from gaining access to your 5G NR data.

• Are the 5G NR devices future-proof? 
Over time, organizations are likely to want to upgrade their applications. In addition, the 5G NR specification is not set in stone, and updates to it are made periodically. Organizations will want to ensure their 5G NR edge devices are futureproof, with capabilities that include the ability to update them with new firmware over the air, so they can upgrade their applications and take advantage of new 5G NR capabilities in the future. 

• Can the 5G NR device do edge processing? 
While 5G NR increases the amount of data that can be transmitted over cellular wireless networks, in many cases organizations will want to filter, prioritize, or otherwise process some of their 5G NR application’s data at the edge. This edge processing can enable these organizations to lower their data transmission costs, improve application performance, and lower their devices energy use. 

5G NR edge devices that offer organizations the ability to easily process data at the edge allow them to lower their data transmission expenses, optimize application performance, and maximize their devices’ battery lives. 

Originally posted here.

Augmented Reality not only enhances reality through virtual and bundled information, but also offers untapped opportunities for companies and their customers. This technology can significantly support customers in processing information more efficiently and relieve them cognitively. Early adopters such as Amazon and IKEA are already using augmented reality in online shopping for product demonstrations. This gives customers a more comprehensive insight into the product, which supports their purchase intention. Industry is already using the technology in a more versatile way and exploiting the advantages, for example, in engineering, in production, in service or for employee training. This justifiably raises the question of why this potential of AR is not also being exploited at the customer level.

For customer participation, it would be groundbreaking to reliably empower customers in their contribution to involvement, regardless of their skills and prior knowledge. In the future, customers would no longer have to bother with paper instructions when assembling furniture but would be able to follow work instructions more easily using their smartphones. This can also be applied to other everyday situations, such as repairing one's own bicycle or helping to indicate a malfunction in the heating system when it displays a message again.

The examples listed all have the common feature that AR acts as a medium for guided work instructions so that customers can be supported more efficiently in their actions. As an expert in the field of AR and IoT, I have questioned at this point whether there really an increase in efficiency is, how this possible increase in efficiency makes itself felt, and how the effects could be explained. To get to the bottom of the problem, an empirical survey was designed in which a 26-step assembly task had to be accomplished. The test persons were divided into two groups. While the experimental group received instructions in an AR app via iPad, the control group worked with classic paper instructions. After the experiment, all participants were asked about their subjective perceptions during assembly using a standardized questionnaire.

The results of the empirical study are in line with the media perception or hype of augmented reality. The members of the experimental group had a significantly shorter processing time, made significantly fewer errors and were more satisfied overall with the assembly task. Based on the subjective perception of our test subjects, it can be shown that the increase in efficiency on the part of the experimental group can be explained by a reduction in their cognitive load.

Overall, the survey not only reveals efficiency gains using augmented reality, but also raises the prospect of other factors. The participants were more efficient in their actions and were also significantly more satisfied with the process. According to existing marketing literature on satisfaction, it follows that there is an increased repurchase intention, an increased willingness to pay, positive eWOM, and sustained customer loyalty. It can be shown that the use of augmented reality can not only reduce existing costs by increasing efficiency but promises additional revenue. With the advancement of technical realities in private households, the use of AR at the consumer level is no longer a utopia. The technology is ready! So, are you?

Look around you, and you’ll find at least 4 objects in your house with the word ‘smart’. Your TV, your phone, maybe even your fridge. All of our appliances are increasingly being connected to the internet.

This interconnection of ‘smart’ objects is referred to as the Internet of Things (IoT). In less than a decade, we’ve pushed communication technology to its limits.

Now you can talk to your microwave from your phone. With over 20 billion devices part of the IoT phenomenon, our lives are more connected than ever before. But, there's a flip side to this technological revolution.

There are a lot of IoT security risks that arise from the vulnerabilities of the devices. Over 200 million individual IoT attacks were tracked in 2020 alone.

Hackers can take advantage of vulnerabilities to steal your data, or to use your devices to conduct attacks. This blog will take you through the procedures you can adopt to secure your life from cybercriminals.

Overview of IoT

Internet Protocol Version 4 (IPv4) is the protocol that is the process through which our devices connect with the internet.

When the internet is accessed, a unique identity protocol is generated Recently, however, IPv4 has been running out of physical addresses. To fix this, IPv6 was introduced that has the capacity for trillions of trillions of physical addresses. It also offers improvements to connectivity, performance, and security. 

IoT has already been used extensively to provide ease to human life, with some of the many applications being innocuous.

• Home Automation - Phones are now being used to connect with most homes to your electric circuits, your TV, AC Fridge, and more. This has simplified lives while improving productivity and efficiency. Many of these devices also optimise themselves, for instance, an AC that adjusts temperature itself based on the environment.
• Smart Cities - By far the most awaited feature of IoT. Smart Cities promise to revolutionize the way you live. Not only will they reduce costs, but they would also improve efficiency. Road signals would be able to manage traffic congestions, and parking sensors would inform you of empty spots.
• Drones - Drones are increasingly being used to simplify our lives. Right from being used by Amazon as delivery agents, to being used by government bodies for firefighting activities, drones are revolutionizing the tech space.
• Medical Applications - Smartwatches monitor a person’s health and can call them an ambulance when at risk. Ambulances that can connect to the road signals and clear a path. 
• Smart Phones - Your phone will most likely be the key to controlling the IoT. Already many appliances connect to your phone, and many more may soon follow. VR and AR have made great leaps forward, allowing people to do much more than simply call people with their phones.

Threats of IoT

IoT suffers from similar vulnerabilities that hackers attempt to use to their advantage. They use these devices to either steal personal data or to connect them to a botnet. According to Symantec, IoT attacks have increased a 1000% since 2016, with routers and security cameras being the most attacked.

• Botnet - A botnet is essentially a large collection of IoT that hackers can be used to make large coordinated attacks on other services. Botnets are easy to create, with IoT being a favored target due to their weaker security.
• Shadow IoT - Losing control of your devices can be terrifying. Researchers have already proved it possible to stall the engines of smart cars too. Many industries use SCADA systems, a massive computer overseer. Were this to be compromised, it could lead to catastrophe, including nuclear meltdowns in the worst case. 
• Data Theft - The most common threat. Data can be extracted not only from the compromised device but all on the network. This can be catastrophic for your business. Losing the data of millions of users can erode their trust in your services. 

Applying Penetration Testing to circumvent IoT Attacks

Thankfully, there are ways in which firms protect themselves from IoT Security risks. Using penetration testing (pen testing), a simulated attack on your device, you can identify vulnerabilities and fix them before an actual attack hit. Pen testing will search for a range of vulnerabilities, ranging from but not limited to,

1. Weak passwords: passwords that can be guessed or opened through trial and error.
2. Hardcoded passwords: Public passwords that cannot be changed, such as firmware backdoors and client software.  
3. Network services: This helps the devices on the network to communicate and share information. 
4. Ecosystem Interfaces: Authentication, encryption issues, and input/output filtering problems arising from the device’s connections. These could be the internet, the backend API, the cloud, or other devices.
5. Updates: The ability to receive and apply updates to firmware, security, and provide warnings for security changes. 
6. Components: Insecure or outdated components such as software, libraries, customization, third-party apps, etc.  
7. Privacy: Data that can be leaked due to a device on the network not being configured with the proper controls.
8. Data Security: Data encryption and access control during storage, transit, and processing to prevent hijacks between connections. 
9. Default Settings: Insecure default settings that might still be on the device.
10. Physical Hardening: Physical hardening measures to prevent hackers from scoping devices or taking local control of devices. 

Your business must be secure and Pen testing is a great way of identifying these vulnerabilities, which you can then rectify.

Here's how firms can go about it. 

• Identify Devices on The Network - The first step to protecting yourself is to identify which devices are actually on the network. As the network gets bigger, it can be harder to keep track of the devices. Don’t hesitate to pull back, take stock, and remove devices you don’t think need to be on the network.
• Implement Strong Passwords - Without saying, this is the single most important tip. Always ensure your password is not something related to your personal information, such as your full name. Vary your password with numbers and symbols. And don’t use the same password everywhere!
• Download The Latest Security Updates - As attacks increase, so does the defines. Many manufacturers release new updates that patch IoT vulnerabilities. Staying up to date can prevent older attacks from getting through.
• Install Firewalls - Firewalls will prevent unauthorized access through the network. Intrusion detection systems/intrusion prevention systems (IDS/IPS) should be run to monitor and analyse network traffic. Firewalls also have the added benefit of warning you of unauthorized access. This can be the first sign of a breach in security.

IoT has a lot of potential for making human life convenient and efficient. However, it is advisable to take your time with implementing new technologies, make sure you have all the risks covered.

Rigorous testing should be your motto before introducing anything new to your business. Security should be your main priority. 

Introduction   

Over the years, there has been an extensive shift of digitalization that has called for new concepts and new technologies. Especially when it comes to improving human life and reducing effort in routine tasks, one thing that has gained immense popularity is the very idea of IoT.   

The Internet of Things (IoT) is a network of physical objects (vehicles, devices, buildings, and other items) embedded with software sensors, electronics, and network connectivity to collect and exchange data. It is the network of those inter-connected objects or smart devices that can exchange information using a method of agreement and data schema.    

According to Statista, the total installed base of IoT (Internet of Things) connected devices worldwide estimated to reach 30.9 billion units by 2025, a significant increase from the 13.8 billion units anticipated in 2021.    

Common Challenges in IoT    

Do you know how IoT works? Well, IoT devices are capable of providing automated facilities because they have inbuilt sensors and mini-computer processors, in which sensors collect the data with the help of machine learning. But unfortunately, these devices are connected to the internet and are more vulnerable to hacking and malware.    

Nevertheless, we are living in the digital world where your car will soon be a better driver than you, and your smart security systems will provide:  

• Better protection to your residence,   
• Your Industries,   
• and your commercial places against damage and theft.  

Your smart refrigerators will better communicate with the internet. It will be more responsible for ordering your grocery items. All these miracles can happen with automation and the advancements of embedded systems into the Internet of Things.    

However, improving the performance and quality of such systems is a significant challenge because IoT devices generate a large variety and volume of data that are difficult to test if the IoT testing service provider that you’ve hired for testing doesn’t have the best resources, tools, test environments, and test methods to ensure the quality, performance, speed, and scalability of such systems. Consequently, IoT testing services are the key to ensuring flawless performance and functionality of your IoT systems.   

As long as it comes to testing of IoT devices, organizations face severe challenges that you can discover below:   

Testing Across Several Cloud IoT Platforms    

Every IoT device has its own hardware, and this device is dependent on software to operate it. When it comes to integration, IoT devices require application software to run commands to the devices and analyze data collected by the devices. Also, each device comes with different operating systems, versions, firmware, hardware, and software, which may not be possible to test with various combinations of devices.    

Before conducting testing on IoT devices, one needs to collect information from the end-users about which software they’re using to run the IoT devices. One of the most widely used cloud IoT platforms that assist in connecting different components of the IoT value chain is IBM Watson, Azure IoT, and AWS, among others. To run IoT devices across all cloud IoT platforms, it is necessary to consider the experienced IoT testing service provider or experts from the software testing company, mainly those who are well-versed in the testing of cloud IoT platforms and can ensure their practical usability.    

One should know about an IoT environment and understand how devices generate data with a wide variety, velocity, and veracity. Make sure IoT devices produce the data into a structured or unstructured form and then send the enormous amounts of data to the cloud. If you plan to get IoT testing services, you need to test your IoT application across various platforms. Testing should be performed in a real-time environment. If the device often introduces firmware updates or new version upgrades, it is crucial to perform specific testing by keeping all such factors in mind.    

Data Security Threats    

The volume of data gathered and communicated by connected devices is enormous. The higher amount of data generated by devices, the higher number of data leaks or any other risks your system can experience from outside entries.    

Testing of IoT devices is vital from the best IoT testing service provider. Otherwise, your IoT device can become vulnerable to security threats. With QA experts or IoT testing services, you can quickly identify security bottlenecks from the system and address them early as possible.    

When performing IoT testing, it is necessary to test credentials, passwords, and data interface to ensure that there are no risks for security breaches. Today, IoT engineers implement layered security, and with this process, they can get multiple levels of protection for the system and prevent the system from potential attacks or data leaks.  

 Too Many IoT Communication Protocols    

Nowadays, IoT devices use several distinct communication protocols from Message Queuing Telemetry Transport (MQTT), Constrained Application Protocol (CoAP), and common Extensible Messaging and Presence Protocol (XMPP) to interact with controllers and with each other.    

But the most popular protocol that ensures the IoT device will communicate and perform well even in high latency and low bandwidth situations is MQTT (Message Queuing Telemetry Transport (MQTT).  

However, due to the popularity of MQTT, it is crucial to ensure the security of this protocol as it is open to attacks and doesn’t provide excellent protection beyond the Transmission Control Protocol layer. Therefore, one should hire a diligent IoT testing service provider to assure that testing will perform rigorously. In addition, it ensures that the communication between controllers and disparate devices will happen more reliably and safely.    

Lack of Standardization    

Due to the increasing number of connected devices, it becomes imperative to improve the standardization of an IoT system in different levels: platforms, standard business models, connectivity, and application.    

Standardization for each IoT device should be uniformed while testing. Otherwise, your users can face severe problems at the time of connecting IoT devices with different systems.    

For this, the IoT testing service provider should have detailed expertise in performing connected device testing based on the intended use or use case of the system. Also, there should be a uniform standardization for all levels of IoT systems before providing quality-based IoT products to end-users.    

Conclusion    

IoT testing approach can vary based on the architecture or system involved. Therefore, businesses should focus more on reliable IoT testing services and allow testers to focus more on the Test-As-a-User (TAAS) approach instead of testing based on the requirements.   

Always choose the trustworthy IoT testing service provider for integration testing of IoT systems. One should have a comprehensive strategy to discover the bugs in the system through integration testing.   

Numerous challenges occur while implementing IoT testing, but it is an exciting job if the testing service provider is ready to offer you end-to-end functional and non-functional validation services for different implementations.    

The company should be certified to test IoT connected devices with a complicated mesh of devices, hardware, protocols, operating systems, firmware, etc. In addition, they should have industry best practices with IoT testing tools to address challenges that you face every day while using IoT systems.    

This webinar series will take you through the fundamental steps, tools and opportunities for simplifying IoT development.

WEBINAR SERIES:   Fast and Fearless - The Future of IoT Software Development SUMMARY The IoT is transforming the software landscape. What was a relatively straightforward embedded software stack, has been revolutionized due to the IoT where developers juggle specialized workloads, security, machine learning, real-time connectivity, managing devices in the field - the list goes on. How can our industry help developers prototype ‘fearlessly’ because the tools and platforms allow them to navigate varying IoT components? How can developers move to production quickly, capitalizing on innovation opportunities in emerging IoT markets?  This webinar series will take you through the fundamental steps, tools and opportunities for simplifying IoT development. Each webinar will be a panel discussion with industry experts who will share their experience and development tips on the below topics. Part One of Four: The IoT Software Developer Experience Date: Tuesday, May 11, 2021 Webinar Recording Available Here Part Two of Four: AI and IoT Innovation Date: Tuesday, June 29, 2021 Time: 8:00 am PDT/ 3:00 pm UTC Duration: 60 minutes Click Here to Register for Part Two Part Three of Four: Making the Most of IoT Connectivity Date: Tuesday, September 28, 2021 Time: 8:00 am PDT/ 3:00 pm UTC Duration: 60 minutes Click Here to Register for Part Three Part Four of Four: IoT Security Solidified and Simplified Date: Tuesday, November 16, 2021 Time: 8:00 am PDT/ 3:00 pm UTC Duration: 60 minutes Click Here to Register for Part Four

It’s no secret that I love just about everything to do with what we now refer to as STEM; that is, science, technology, engineering, and math. When I was a kid, my parents gifted me with what was, at that time, a state-of-the-art educational electronics kit containing a collection of basic components (resistors, capacitors, inductors), a teensy loudspeaker, some small (6-volt) incandescent bulbs… that sort of thing. Everything was connected using a patch-board of springs (a bit like the 130-in-1 Electronic Playground from SparkFun).

The funny thing is, now that I come to look back on it, most electronics systems in the real world at that time weren’t all that much more sophisticated than my kit. In our house, for example, we had one small vacuum tube-based black-and-white television in the family room and one rotary-dial telephone that was hardwired to the wall in the hallway. We never even dreamed of color televisions and I would have laughed my socks off if you’d told me that the day would come when we’d have high-definition color televisions in almost every room in the house, smart phones so small you could carry them your pocket and use them to take photos and videos and make calls around the world, smart devices that you could control with your voice and that would speak back to you… the list goes on.

Now, of course, we have the Internet of Things (IoT), which boasts more “things” than you can throw a stick at (according to Statista, there were ~22 billion IoT devices in 2018, there will be ~38 billion in 2025, and there are expected to be ~50 billion by 2030).

One of the decisions required when embarking on an IoT deployment pertains to connectivity. Some devices are hardwired, many use Bluetooth or Wi-Fi or some form of wireless mesh, and many more employ cellular technology as their connectivity solution of choice.

In order to connect to a cellular network, the IoT device must include some form of subscriber identity module (SIM). Over the years, the original SIMs (which originated circa 1991) evolved in various ways. A few years ago, the industry saw the introduction of embedded SIM (eSIM) technology. Now, the next-generation integrated SIM (iSIM) is poised to shake the IoT world once more.

“But what is iSIM,” I hear you cry. Well, I’m glad you asked because, by some strange quirk of fate, I’ve been invited to host a panel discussion — Accelerating Innovation on the IoT Edge with Integrated SIM (iSIM) — which is being held under the august auspices of IotCentral.io

In this webinar — which will be held on Thursday 20 May 2021 from 10:00 a.m. to 11:00 a.m. CDT — I will be joined by four industry gurus to discuss how cellular IoT is changing and how to navigate through the cornucopia of SIM, eSIM, and iSIM options to decide what’s best for your product. As part of this, we will see quick-start tools and cool demos that can move you from concept to product. Also (and of particular interest to your humble narrator), we will experience the supercharge potential of TinyML and iSIM.

Panel members Loic Bonvarlet (upper left), Brian Partridge (upper right),

Dr. Juan Nogueira (lower left), and Jan Jongboom (bottom right)

The gurus in question (and whom I will be questioning) are Loic Bonvarlet, VP Product and Marketing at Kigen; Brian Partridge, Research Director for Infrastructure and Cloud Technologies at 451 Research; Dr. Juan Nogueira, Senior Director, Connectivity, Global Technology Team at FLEX; and Jan Jongboom, CTO and Co-Founder at Edge Impulse.

So, what say you? Dare I hope that we will have the pleasure of your company and that you will be able to join us to (a) tease your auditory input systems with our discussions and (b) join our question-and-answer free-for-all at the end?

Video recording available:

Internet of Things is a buzzword that is trained to blend itself in today's market seamlessly. But do you know what it is? Also, what does it signify for the delivery sector? IoT mainly refers to the concept of connecting various devices and transferring data using wireless apps. It eliminates face-to-face human interaction to a great extent.

The Internet of Things guarantees big things in the world of customer goods, but even more significant things in the evolution of the supply chain. Research firm Gartner stated that IoT would change the world of delivery services. A thirty-fold increase in Internet-connected physical machines by 2020 will significantly alter how the sector works. Morgan Stanley concludes that 75 billion devices will be connected with IoT-enabled devices by the end of 2020.

With today's growing customer demands for personalized and speedy service, it's no surprise IoT is evolving rapidly; this is special for the delivery and logistics sector. With IoT becoming more accepted globally, more devices are designed with sensors that can be monitored, opening up countless opportunities for those that choose to board the growing trend. With the advanced technology to carve a position in the delivery market, it's fascinating to keep an eye on how the sector ecosystem transforms and the type effects on system and operations.

Food Delivery with IoT: Explore How it Enhances Business Operations!

The IoT is quickly widespread in the food delivery sector. It has been primarily driven by pizza chains, including Pizza Hut, Dominos, and many more. Using smart devices, a customer can easily order mouth-watering pizza, get an estimated time for delivery, get a real-time update, watch the order being made through a webcam, etc.

Delivery personnel if knowing the exact delivery location can eliminate time lost to confusing addresses. Tipping and payment can also be handled through feature-rich solutions, making the process more efficient. The best part is that delivery brands like UberEats are leveraging the advantage of IoT technology.

Image: (Source)

MarketsandMarkets determined the global IoT market size is valued at 170.6 billion in 2017. It's presumed to reach 561.0 billion by the end of 2022, at a 26.9% Compound Annual Growth Rate during the predicted period. The report scope covers the internet of things market by platform, software solution, services, apps region, and area.

Image: (Source)

The software solution is divided into remote monitoring, real-time streaming analytics, data management, network bandwidth management, and security solution. However, it's further segmented into developing home automation, smart manufacturing, energy, retail, mobility, and transportation.

Image: (Source)

The simple deployment and low-cost process of IoT-powered devices mean virtually any restaurant service that can provide smart delivery. However, numerous restaurants, including local chains, are lacking to take advantage of and opportunities IoT provides to them. A restaurateur can provide turnkey with smart IoT-enabled solutions, helping to complete and manage every business operation effectively.

Impact of IoT On Delivery Industry

With ever-growing customer demands for personalized and speedy service, it is no wonder the IoT is increasing, especially in the logistics and delivery sector. However, the IoT will allow troubleshooting and greater accuracy throughout the fully automated methods, significantly reducing the brand's required work hours.

With IoT existing is accepted globally, more devices are developing with sensors that can be tracked, thereby opening up countless opportunities. Machine-to-Machine and IoT interaction are evolving customer expectations around the delivery sector, forcing providers to replan and know how they can do more business and generate more leads in less time.

Increases Operational Visibility

In the delivery sector, operational visibility is critical for developing faster and more efficient actions. Luckily improved visibility is the primary benefit the IoT technology brings to your table. The restaurateur can obtain valuable insight into accurate data-driven decisions and operations.

Building a well-integrated IoT platform at your place can provide the fleet manager with information and a deeper understanding of data like on-time deliveries, real-time alerts, and more. All the data provided by managers possess the ability to decrease unnecessary problems that can otherwise arise. In simple terms, an IoT system permits data-driven judgments to occur and reduces unexpected problems; all this reduces extra cost throughout the delivery process.

Moreover, in terms of warehouse services, IoT streamlines operations with sensors, bar code readers, etc., ensuring to provide you with visibility of inventory and tracing of products and services quickly and efficiently. In essence, business managers can easily understand what products they have to make snap decisions accordingly.

Route Optimisation

Visibility is critical for delivery brands wishing to thrive in a competitive market, but it's not only one factor why brands must consider IoT integration. Inefficient and unorganized routes can result in a downfall; such routes increase fuel use, road time, carbon footprints, and other resources. However, this dramatically affects the company's bottom line as well as the operational environment.

However, IoT-enabled devices are fighting all of this by strategically utilizing corporation resources to relinquish all planned destinations and open interaction between fleet managers and drivers. It improves real-time analytics and helps to achieve an efficient system of operations and manage consumer satisfaction.

Improves Real-Time Tracking

Every delivery business understands the stress of managing multiple deliveries at a time. However, a restaurateur can develop food delivery apps using IoT technology, helping them to stay aware of the real-time location of drivers and deliveries. It helps them to deal with unexpected problems that sometimes occur on the road.

The data enables restaurateurs to drive accurate and intelligent decision-making, ensuring to improve customer service by keeping customers updated about the delivery service. Most brands these days are using RFID and are approaching about 100% receiving accuracy, 33% faster order processing whereas 30% reduction in operational costs."

Efficient Last-Mile Delivery

Due to customer demand and delivery growth, many complex challenges are created for a restaurateur to tackle. Most of the challenges arise due to last-mile delivery due to driver behavior, traffic, driver behavior, etc. However, IoT is helping supermarkets and restaurants at every stage, helping them replan their operation process and ensure a streamlined journey for customers.

Hence restaurateur needs to find a cost-effective platform that satisfies customer needs and unexpected problems. Modern technology enables them to bridge the gap between customers and driver inter-communication, ensuring business growth.

Preventive Maintenance

Additionally, if you want to gain better insight into delivery provider behavior, you can connect all your vehicles. It even helps with preventive maintenance for the vehicle. IoT-connected vehicles will send automated signals and warning alerts when any part of a particular vehicle requires maintenance. 

With the help of such alters, you can easily maintain services such as a low battery, coolant temperature, check engine, etc., ensuring to leverage preventive maintenance and increasing the lifespan of your vehicles.

Wrapping It Up

The delivery sector is experiencing a lot of change with the IoT, and it seems to have more improvements shortly as well. The advantages of IoT in the delivery industry are indisputable, and as more and more devices are connected, further optimizations show that the numbers will grow. 

The urgency of IoT adoption differs from one sector to another and its impact as well. But it has excellent benefits for the delivery sector as it provides excellent visibility, reduces operation cost, and better last-mile execution. Hence considering integrating IoT within your business process is a wise choice that will bring worth for your business.

Happy Friday (or whatever day it is when you find yourself reading this). I’m currently bouncing off the walls in excitement because I’ve been invited to host a panel discussion as part of a webinar series — Fast and Fearless: The Future of IoT Software Development — being held under the august auspices of IoTCentral.io

Panel members Joe Alderson (upper left), Pamela Cortez (upper right), Katherine Scott (lower left), and Ihor Dvoretskyi (bottom right)

At this event, the first of a 4-part series, we will be focusing on “The IoT Software Developer Experience.”

As we all know, the IoT is transforming the software landscape. What used to be a relatively straightforward embedded software stack has been revolutionized by the IoT, with developers now having to juggle specialized workloads, security, machine learning, real-time connectivity, managing devices that have been deployed into the field… the list goes on.

In this webinar — which will be held on Tuesday 11 May 2021 from 10:00 a.m. to 11:00 a.m. CDT — I will be joined by four industry luminaries to discuss the development challenges engineers are facing today, how the industry is helping to make IoT development easier, an overview of development processes (including cloud-based continuous integration (CI) workflows and low-code development), and what the future looks like for developers who are building for the IoT. 

The luminaries in question (and whom I will be questioning) are Joe Alderson (Director of Embedded Tools and User Experience at Arm), Pamela Cortez (IoT Developer Advocate and Sr. Program Manager at Microsoft Azure IoT), Katherine Scott, Developer Advocate at Open Robotics, and Ihor Dvoretskyi (Developer Advocate at Cloud Native Computing Foundation).

So, what say you? Dare I hope that we will have the pleasure of your company and that you will be able to join us to (a) tease your auditory input systems with our discussions and (b) join our question-and-answer free-for-all at the end?

Recording available:

Well, this isn’t something I expected to be talking about today, but my chum Ben Cook just introduced me to something that looks rather cool.

Ben is the Founder and Director at Airspeed Electronics Ltd., which is an electronic design consultancy that’s based in the UK specializing in high-performance acoustic detection and tracking technology for counter-unmanned aircraft system (UAS) applications. The folks at Airspeed Electronics are currently developing a drone detection and tracking system called MANTIS, where this work is being funded through a research grant provided by the UK Ministry of Defence (which — before you make a nasty comment — is how they spell “Defense” in the UK).

MANTIS, which stands for “MAchine learNing acousTIc Surveillance,” is a system of distributed, intelligent acoustic sensors that use artificial intelligence (AI) for the detection, classification, and location estimation of UAS — such as drones — based on their acoustic signatures.

But that’s not what I wanted to talk to you about…

In his email to me, Ben spake as follows: “Have you heard of an embedded operating system called ‘Luos’ before? It’s a microservices software architecture, like docker but for use with microcontrollers. I have no affiliation, I just stumbled across this today and I’m thinking this could be very useful for some future projects. It looks really good for anything ‘modular-y,’ if you know what I mean…”

I do know what Ben means. I just meandered my way around the luos.io website, perused and pondered the documentation at docs.luos.io, and watched this video on YouTube (later today, I’m going to get the tattoo, buy the T-shirt, and see the stage play).

In a nutshell, Luos is a simple and lightweight open-source distributed operating system dedicated to embedded systems. It uses the concept of modularity to simplify the linking of components and chunks of application code together to form a single system image.

Consider a system like a robot that uses multiple microcontrollers to manage its various sensors, actuators, and motors. If each of these microcontrollers employs Luos technology, all of them can use any feature of any microcontroller in the system as if all of the features were located in the same component.

Now, I’m a hardware design engineer by trade, so the software side is a bit outside my bailiwick, but — even so — looking at the video above and scanning the documentation makes me sit up and say, “Wow, this looks really, really cool.”

I asked around a few of my embedded systems software developer friends, and no one had heard of Luos, but I have a feeling that this may be a tool that’s poised to make a big splash. All sorts of ideas are currently bouncing around my head, like the fact that the Tracealyzer tool from Percepio would make an ideal companion for the Luos OS (see also The 2021 Embedded Online Conference Approacheth).

How about you? Have you heard of Luos? If so, what are your thoughts? If not, and if you lean toward the software side of things, it would be great if you could take a look with your highly trained eye, see what you think, and report back to the rest of us in the comments below.

Originally posted HERE. 

The world has seen the emergence of countless advanced technologies over the past few decades and among them, one of the most notable and impactful has been the Internet of Things. Often described as a critical part of the foundation of our technology-driven future, IoT has shaken up pretty much every industry on the face of Earth. For the better, of course. Anyway, this transformation brought on by IoT has made its way into the world of web and mobile apps development too, and understandably so. After all, today apps are not only the most omnipresent modern tools but are relied upon by millions and millions of people every single day. Suffice it to say that app development is vital to the cause of keeping the world running and IoT has only entered the scene to further improve things. But the question remains: How?

The Internet of Things is a dynamic technology that has, for starters, completely changed how users in the digital realm interact and engage with web applications as well as mobile applications. It not only enables companies to effortlessly deal with humongous volumes of data, but also ensures top-notch security, seamless communications, and so much more. After all, the Internet of Things market is not projected to touch $11 trillion in economic value by 2025 without reason. Studies have also found that the global investment in IoT could touch $15 trillion by 2025. Now, let’s explore some of its other contributions to app development in detail.

1. Smarter UIs: While it can be quite challenging to put together UIs that integrate modern technologies and still successfully tend to users’ expectations, IoT can help considerably in this regard. It is highly conducive to the development of effective UI and integrates relevant latest trends to further enhance users’ experiences while engaging with the app. Oh, and let’s not forget that it also enables A/B split tests to help developers identify which iteration of the app is best suited for success.
2. Cybersecurity: Of course, ensuring high levels of security with your apps is a top priority for everyone. IoT helps ameliorate this process by helping programmers to integrate the latest security measures and strategies. This includes modern identification and authorization methods to monitor the continued safety of all the data stored within the app.
3. Chatbots: Now, artificial intelligence and machine learning-driven chatbots can be further integrated with the Internet of Things to empower them with access to even more sources of data. This, then, allows them to answer customers' queries and issues in a much more proficient manner, which is critical to ensuring high levels of customer satisfaction in an increasingly competitive market.
4. Data collection and processing: Data collection and its processing are critical to the success of any app in the world today. With the Internet of Things, that ability is fortified since one now gains access to a wider set of sources for data. Furthermore, IoT also helps avoid any lags in the relay of this information, thus enabling it to be used in real-time.

There is not even a shred of doubt that avant-garde technologies such as the Internet of Things, artificial intelligence, machine learning, etc. have completely transformed the web and mobile app development process and for good! So, if you want to take advantage of IoT and other such technologies to build modern apps that are more secure, highly customer experience-focused, and enable the seamless collection of data among other things, all you have to do is find a qualified service provider for their development. Their expertise and knowledge will further fortify your product and thus, your customers’ experiences.