Air quality monitoring has been increasingly important over the years. The use cases for monitoring air quality include both indoors and outdoors. Monitoring the air is also not just for human health, monitoring air quality in regards to temperature, humidly and more can be important for building maintenance, agriculture and any environment where the air affects it’s surroundings. Let’s walk through some of the core factors in smart air monitoring:

Accuracy: One of the most important factors of smart air quality monitoring is accuracy. It is important that the sensors used are able to detect even small changes in air quality. This means that the sensors need to be sensitive enough to detect even low levels of pollutants. Additionally, the sensors need to be reliable and consistent in their measurements.

Connectivity: Smart air quality monitoring systems need to be able to connect to the internet and transmit data in real-time. This is essential for providing up-to-date information about air quality to users. Additionally, it allows for the collection of large amounts of data, which can be used to identify trends and patterns in air quality.

Accessibility: Smart air quality monitoring systems need to be accessible to everyone, regardless of their technical ability. This means that they need to be easy to set up and use, with clear instructions provided. Additionally, they need to be affordable, so that they can be used by people on all income levels.

Integration: Smart air quality monitoring systems need to be able to integrate with other systems and devices. For example, they may need to be able to connect to smart home devices, such as thermostats, to automatically adjust settings based on air quality data. Additionally, they may need to integrate with public health systems to provide real-time data to medical professionals.

Battery Life: Smart air quality monitoring systems need to be able to operate for extended periods of time without needing to be recharged or replaced. This is especially important for outdoor sensors, which may be located in remote areas. Battery life can be extended by using low-power sensors and optimizing the power usage of the device. 

User Interface: Smart air quality monitoring systems need to have a user-friendly interface that allows users to quickly and easily access the information they need. This may include a mobile app or a web interface that displays air quality data in a clear and understandable format. Additionally, the interface should allow users to set up alerts when air quality reaches certain levels.

Data Visualization: Smart air quality monitoring systems need to be able to display data in a way that is easy to understand. This may include graphs, charts, and other visualizations that show trends over time. Additionally, the system should allow users to customize the way that data is displayed to best suit their needs.

Developers and engineers should consider these factors when planning and operating smart air quality monitoring systems for them to be effective.  

In recent years, the manufacturing industry has undergone a major shift in its approach toward production. The implementation of IoT (Internet of Things) solutions have revolutionized the way factories operate and has brought about numerous benefits to the manufacturing process. In this article, we will discuss the top 10 benefits of IoT solutions in the manufacturing industry.

Benefits of IoT Solutions in Manufacturing Industry

1. Enhanced Productivity

IoT solutions have greatly improved the productivity of manufacturing facilities. Connected devices and sensors work together to streamline the manufacturing process, reducing the time it takes to produce a product. IoT technology allows manufacturers to monitor and optimize their production lines, leading to more efficient and effective operations.

2. Predictive Maintenance

IoT solutions allow manufacturers to monitor their equipment and machinery in real time. This real-time data can be used to predict when equipment will fail and prevent downtime. Predictive maintenance reduces the costs associated with unplanned downtime and maintenance, ultimately improving the bottom line of the manufacturing facility.

3. Improved Quality Control

IoT solutions enable manufacturers to monitor the quality of their products throughout the production process. This helps to identify potential issues early on, reducing the number of defective products that reach the end consumer. Improved quality control leads to increased customer satisfaction and reduced costs associated with returns and warranty claims.

4. Increased Safety

IoT solutions can improve the safety of workers in manufacturing facilities. Connected sensors and devices can monitor the work environment and identify potential hazards. This data can be used to implement safety protocols and prevent accidents from occurring.

5. Supply Chain Optimization

IoT solutions enable manufacturers to track their inventory and supply chain in real time. This allows for better supply chain optimization, reducing costs associated with excess inventory and stockouts. Real-time inventory tracking also enables manufacturers to respond quickly to changes in demand, reducing lead times and improving customer satisfaction.

6. Energy Efficiency

IoT solutions can help manufacturing facilities reduce their energy consumption. Connected sensors can monitor energy usage in real-time, identifying areas where energy is being wasted. This data can be used to implement energy-saving measures, reducing energy costs and improving the environmental impact of the facility.

7. Improved Communication

IoT solutions can improve communication between different departments within the manufacturing facility. Connected devices and sensors can share data in real-time, allowing for better collaboration and coordination. Improved communication leads to more efficient operations and better decision-making.

8. Increased Flexibility

IoT solutions can improve the flexibility of manufacturing facilities. Connected devices and sensors can be used to reconfigure production lines quickly, allowing for rapid changes in production. This leads to more responsive manufacturing operations and the ability to quickly adapt to changing market conditions.

9. Cost Reduction

IoT solutions can help manufacturing facilities reduce their costs. By improving productivity, reducing downtime, improving quality control, and optimizing the supply chain, IoT solutions can have a significant impact on the bottom line of the facility. This ultimately leads to improved profitability and a stronger competitive position.

10. Competitive Advantage

IoT solutions can provide manufacturing facilities with a competitive advantage. By implementing cutting-edge technology, manufacturers can differentiate themselves from their competitors and offer unique value propositions to their customers. This can help to attract new customers and retain existing ones.

Statistics of IoT Solutions in Manufacturing Industry

As these statistics demonstrate, IoT solutions are becoming increasingly prevalent in the manufacturing industry, with significant growth expected in the coming years. The most common use cases for IoT in manufacturing are centered around improving efficiency, reducing downtime, and optimizing supply chains. With such a large potential market size, it's no surprise that more and more manufacturers are investing in IoT technologies to drive innovation and stay competitive.

Final Words

The implementation of IoT solutions in the manufacturing industry brings about numerous benefits, including enhanced productivity, predictive maintenance, improved quality control, increased safety, supply chain optimization, energy efficiency, improved communication, increased flexibility, cost reduction, and competitive advantage. By leveraging IoT technology, manufacturers can improve their operations and ultimately improve their bottom line.

Keeping your fulfillment process steady is made easier with the use of technology for effective business solutions. Get in touch with Aeologic Technologies right away to see how it can benefit your company.

FAQs

How does IoT technology improve productivity in the manufacturing industry?

IoT technology allows for real-time monitoring and optimization of production lines, reducing the time it takes to produce a product and improving overall efficiency.

How does predictive maintenance work with IoT solutions?

Connected sensors and devices monitor equipment and machinery in real-time, collecting data that can be used to predict when maintenance is needed before equipment fails, reducing the costs associated with unplanned downtime and maintenance.

In recent days, neural networks have become a topic for discussion. But the question still needs to be solved- How can it affect our world today and tomorrow?

The global neural network market's compound annual growth rate (CAGR) is expected to be 26.7% from 2021 to 2030. This means that new areas of application for them might appear soon. The Internet of Things that is IoT, is today's most fascinating and required technological solution for business. Around 61% of companies utilize IoT platforms, and we can anticipate the integration of neural networks into enterprise IoT solutions. This anticipation raises many questions, like what gets such collaboration and how to prepare it. Can we optimize the IoT ecosystem using neural networks, and who will approach such solutions?

What do you understand by a neural network, and how is it beneficial for enterprise IoT?

An artificial neural network that is ANN is a network of artificial neurons striving to simulate the analytical mechanisms taken by the human brain. This type of artificial intelligence includes a range of algorithms that can "learn" from their own experience and improve themselves, which is very different from classical algorithms that are programmed to resolve only specific tasks. Thus, with time, the neural network will remain pertinent and keep on improving.

With the proper implementation, enterprise internet of things (EIoT) and ANN can offer the business the most valuable things: precise analytics and forecasts. In general, it is not possible to compare both. Enterprise IoT is a system that needs software for data analysis, whereas ANN is a component that needs a large amount of data to be operational. Their team naturally controls the analytical tasks; therefore, high-level business tasks are performed most effectively, reducing costs, automating processes, finding new revenue sources, etc.

In the Internet of Things ecosystem, neural networks help in two areas above all:

• Data acquisition via ANN-based machine vision
• Advanced-data analysis

If it needs significant investments to execute ANN in big data analytics solutions, neural network image processing can decrease the cost of the IoT solution. Thus, neural networks improve enterprise IoT solutions, enhance their value, and speed up global adoption.

Which solutions within enterprise IoT can be enhanced using neural networks?

IoT-based visual control

The IoT ecosystem begins with data collection. Data quality impacts the accuracy of the ultimate prediction. If you implement visual control in your production processes, neural networks can boost the quality of products by superseding outdated algorithms. Besides this, they will optimize the EIoT solution. Conventional machine vision systems are pricey as they require the highest resolution cameras to catch minor defects in a product. They come with complex specific software that fails to respond to immediate changes.

Neural networks within machine vision systems can:

• Diminish camera requirements
• Self-learn on your data
• Automate high-speed operations

Indeed, industrial cameras use large-format global shutter sensors having high sensitivity and resolution to develop the highest quality images. Nevertheless, a well-trained ANN starts to identify images with time. It allows them to reduce the technical needs for the camera and ultimately cuts the final cost of the enterprise IoT implementation. You cannot compromise the quality of images to detect small components like parts in circuit boards; however, it is manageable for printing production, completeness checking, or food packaging.

After training, neural networks use massive amounts of data to identify objects from the images. It enables you to customize the EIoT solution and train the ANN to operate specifically with your product by processing your images.

For example, convolutional neural networks are utilized actively in the healthcare industry to detect X-rays and CT scans. The outcome offered by such custom systems is more precise than conventional ones. The capability to process information at high speeds permits the automation of production processes. When the problem or defect is caught, neural networks promptly report it to the operator or launch an intelligent reaction, like automating sorting. Hence, it allows real-time detection and rejection of defective production.

An exclusive example of how ANN is utilized for edge and fog computing. As per PSA, a neural network executed in a machine vision system permits lowering the number of defects by 90% in half a year, whereas production costs are decreased by 30%. Prospective areas for ANN in IoT visual control are quality assurance, sorting, production, collecting, marking, traffic control, and ADAS.

Big data advanced analytics for enterprise IoT:

Today, neural networks allow businesses to grab advantages like predictive maintenance, new revenue flows, asset management, etc. It is possible via deep neural networks (DNN) and the deep Learning (DL) method involving multiple layers for data processing. They detect hidden data trends and valuable information from a significant dataset by employing classification, clustering, and regression. It results in effective business solutions and the facilitation of business applications.

In comparison to traditional models, DL manages with the attributes that are expected for IoT data:

1. Assess the time of taking measurements
2. Resist the high noise of the enterprise IoT data
3. Conduct accurate real-time analysis
4. Determine heterogeneous and discordant data
5. Process a large amount of data

In practice, this implies that you don't require middle solutions to deliver and sort the data in the cloud or to analyze them in real-time. For example, full-cycle metallurgical enterprises can execute one solution to analyze the variable and unstructured data from metal mining, smelting, and final manufacturing products. Airplanes generate about 800TB of data per hour, making it impossible to process it all ideally using conventional analytical systems.

Today, DNN models are successful in the following enterprise IoT applications. 

Healthcare:

Today, it has become easy to predict disease using AI-based IoT systems, and this technology is developing for further improvements. For instance, the latest invention based on the neural network can detect the risk of heart attacks by up to 94.8%. DNN is also helpful in disease detection: the spectrogram of a person's voice received using IoT devices can identify voice pathologies after DNN processing. In general, ANN-based IoT health monitoring systems' accuracy is estimated to be above 85%.

Power consumption:

DL systems in the enterprise Internet of Things have provided results in power demand prediction based on power price forecasting, consumption data, anomaly, power theft detection, and leak detection. Smart meter data analysis permits you to calculate consumption, determine the unusual usage of electricity, and predict with an accuracy of more than 95%, which will help you to adjust energy consumption.

Manufacturing:

Neural networks help to use the most demanded IoT service among manufacturers properly- predictive equipment maintenance. It was ascertained to be a workable practice for mechanical and electrical systems. This network provides accurate real-time status monitoring and predicts proper life rest. Another best example is the recognition of employee activity by taking readings and following in-depth analysis.

Transportation & Logistics:

Deep Learning has made smart transportation systems possible. It offers better traffic congestion management by processing travel time, speed, weather, and occupational parking forecasting. Analytical reports based on vehicle data help to discover dangerous driving and possible issues before the failure happens.

As we know, the previous industries generate heterogeneous data. Therefore, the potential of ANN analytics within EIoT will be unlocked for multiple complicated systems.

When to consider ANN for enterprise IoT:

Till now, research in the field of ANNs been very active, and we cannot foretell all the advantages or pitfalls these solutions will convey. No doubt, neural networks find out correlations, models, and trends better than other algorithms. The IoT ecosystem's data will become more extensive, complex, and diverse with time. So, the development of neural networks is the future of IoT.

For now, we can look into the following features of neural networks for enterprise IoT:

• They suit the IoT ecosystem architecture, substituting alternative solutions with significant advantages.
• Essential for industrial image processing.
• Progressive ANN-based data analytics gets the high-level business value of the enterprise IoT solutions – improves productivity, and exactness, boosts sales, and produces informed business decisions.
• Training the ANN requires time and expenditure but will become fully customizable.
• We cannot conclude it is an affordable solution, but the advantages are priceless if the IoT ecosystem is executed accurately.

Therefore, if you are provided with a neural network as one of the opportunities for executing your idea within the IoT ecosystem, give it a chance. You never know, this solution will become a must-have in the coming years.

Technologies like blockchain, IoT, AR, VR, and AI are playing a big role in transforming the gambling industry. They are changing the way of gambling and players all around the world are liking this innovative approach. 

The Internet of things has added a lot of attraction to casinos because with the help of IoT, offering gambling according to the regulation, to ensure players' safety, secure their assets, data security, and excellent player gaming experience becomes so much easier. Not only the gambling industry but also other various industries have adopted it and collaborating with AI, Crypto, and blockchain gives a new shape to the casino world. According to the study, it is expected more than 41 billion IoT devices will be used by 2027. All digital devices such as smartphones, PCs, digital watches, cameras, and other smart gadgets are examples of IoT.

In this article, we are going to discuss how blockchain and IoT are bringing fruitful results in the gambling industry. And why the demand for blockchain development services is so high in the market.

IoT Basics:

IoT is a network of physical objects that are connected with each other by sensors, software, and other technologies to connect and exchange data in a secure and smooth way over the Internet. IoT is defining the gaming industry with positive and fruitful way. 

Before diving in-depth, let’s know about blockchain and IoT.

Blockchain Basics

The main objective of blockchain is to record data in the form of blocks and all blocks are linked together in a chain. That means blockchain is an immutable ledger where all records are saved but cannot be changed, deleted, or destroyed. 

Basically, it is an advanced database mechanism that offers you high security and transparency. There are four types of blockchains:

• Public blockchain
• Private blockchain
• Hybrid blockchain
• Consortium Blockchain

Lets’ know the positive aspects of Blockchain and IoT in gambling business Industry.

Benefits of Blockchain in Gambling Industry

Here are the reasons for the popularity of blockchain and IoT in gambling world and most games and service providers and online casinos are using both technologies in order to create a difference. 

• High Security
  

Blockchain offers you high-end security and when you make any transaction using cryptocurrencies then it will automatically be added to the distributed ledger and will automatically be added in the whole blocks and entry of new coins is added in the blockchain. 

Blockchain in the casino is offering high security to both players and owners. With its help, there is no need to do registration at casinos and there is no need to validate yourself, and no credit card information is required there. You can do all without sharing your personal data and no one regulates you due to the absence of central authorities.

• Anonymity
  

As we all know that according to a specific location, there are certain rules to regulate online casino business and as a user, you have to follow these rules. But with the help of blockchain, you can enjoy any casino all over the world and you can make payments without facing any issues and no one will know your identity. Cryptocurrency and blockchain are not regulated by any central authority and you can earn huge profits by accessing all casinos all over the world and crypto can be used for payment. 

At present, privacy is everything and you can gamble and make transactions without being noticed by anyone because no one can track you here and you have no need to share your personal information.

• Instant and Cost-effective

Blockchain makes it possible to do fast and instant transactions. As we all know that crypto is based on blockchain and not regulated by a central authority so it means there are no mediators and you can make your transaction in a faster way. And cost-effectiveness is another reason that is making it more popular and it charges less than credit cards, debit cards and traditional platforms. 

• Transparency, Efficiency, and Access
  

When you integrate blockchain in the online gambling industry, then you get transparency and no one can make fraud with you. Like you cannot trust traditional casinos, and online platforms for reliable betting services but on blockchain oriented casinos you can. Because here blockchain maintains all records that are impossible to manipulate. 

You can also enjoy casino games without registration because it uses only your wallet address so it becomes quite easy to access and platform efficiency also improves. 

• Smart chips
  

In online casinos, there is a huge amount of data and managing that is quite a tedious task and thanks to IoT that has made it quite easy and user-friendly. With the help of RFID microchips, all illegal activities have become so minimal. RFID microprocessors have made it possible to take care of all aspects of online casinos.

So, we can say that IoT has increased the security of casinos and now players can enjoy gambling services in an easy way. 

Final Word

This article helps you to know all about the IoT and Blockchain and how they are bringing positive changes in the online casino world and gambling industry. After reading this article, we can say that now players and bettors can enjoy online gambling in an effective way without facing any issues. Now they are paying full attention to gambling without caring about extra issues. You can also invest in the gambling business with the help of a sports betting developmet company.

Cloud computing enables all kinds of smart devices to connect to the Internet and exchange information, which has won the favor of end users and has become a mainstream application trend. Various use cases of cloud computing have been pervasive: for example, the data in the mobile phone can be backed up using cloud services, and the data in the mobile phone can be retrieved from other networked devices through accounts. Complete applications, such as various cloud games, cloud office software, etc., can be accessed directly from a web browser.

At the same time, cloud computing enables companies to complete more computing tasks and data storage through cloud servers in addition to their own physical hardware, eliminating the tedious maintenance process of physical hardware for small and medium-sized teams, and focusing more on their own business.

From wearables to smart home devices to low-level sensor products, connected devices are everywhere. According to relevant statistics from IDC, the global Internet of Things spending will reach 690.47 billion US dollars in 2020, of which the Chinese market accounts for 23.6%. IDC predicts that the global IoT market will reach US$1.1 trillion by 2025, with an average annual compound growth rate of 11.4%, of which the Chinese market share will increase to 25.9%

Smart Home Device Sensors

But centralized cloud computing is not suitable for all applications and use cases. Edge computing can provide solutions in areas where traditional cloud infrastructure may struggle. In recent years, the consolidated and centralized nature of cloud computing has proven cost-effective and flexible, but the rise of the Internet of Things and mobile computing has put a strain on network bandwidth. Ultimately, not all smart devices need to leverage cloud computing to function. In some cases, the round-trip transfer of data even consumes additional resources. As a result, edge computing came into being.

According to relevant information from IDC, edge computing is described as "a mesh network of micro-data centers that process or store critical data locally and push all received data to a central data center or cloud storage repository with a coverage area of less than 100 km." square feet".

Localized data processing and storage puts less pressure on computing networks. When there is less data being sent to the cloud, the likelihood of delays is greatly reduced. This also puts more tasks on the hardware based on edge computing technology, and needs to include sensors to collect data and CPU or GPU units to process data in networked devices.

2019 was the year that IoT solutions started to become a reality. The internet of things has been predicted for years now, but the implementation of IoT solutions has been slower. The impact that IoT will have on business and society cannot be understated, and many companies are aiming to gain a competitive advantage by implementing IoT solutions.

Every year, more entrepreneurs tend to jump on the IoT bandwagon to leverage the benefits of this rapidly evolving technology. Tapping into the IoT, businesses can achieve a plethora of benefits, including increased revenues, better customer services, and enhanced operations. All over the world, companies are turning to the Internet of Things solutions, especially in high-tech industries, such as automotive and aerospace, and in sectors such as manufacturing and retail.

Artificial intelligence and machine learning (AI/ML) deployed on sensors, devices, and networks through the Internet of Things (IoT) are helping enterprises transform the way they do business. Although IoT adoption rates have increased in recent years, IoT adoption is still relatively low. However, by 2025, the number of connected devices will grow to 75.44 billion from 16.2 billion in 2017, according to Statista.

What does IoT mean for digital transformation?

A digital transformation enterprise is not just about the technology or the platform. It is about a new approach to business. IoT is revolutionizing the way enterprises think about their business and the way in which customers and partners interact with them, providing new opportunities for revenue growth and customer engagement.

The Internet of Things (IoT) presents a wealth of opportunities for businesses to transform their processes and operations, leading to more efficient and effective services. By connecting physical devices and systems to each other and the cloud, businesses can gain greater insight into their operations, access real-time data, and automate processes. This can help businesses to save time, money and resources, as well as improve customer experience and reduce operational costs. IoT can also enable new business models, allowing businesses to develop new products and services and create new revenue streams. In short, IoT is an essential part of any digital transformation strategy

Automation: IoT devices can be used to automate tedious and labor-intensive tasks. Automation can be used to streamline processes, increase efficiency and reduce errors, ultimately speeding up the innovation process. can also be used to streamline data collection, allowing businesses to collect and analyze data in real-time to gain valuable insights and make data-driven decisions. This not only accelerates the development process but also reduces the cost associated with data collection and analysis.

Connectivity: IoT devices can be used to connect disparate systems and enable data and information sharing. This can be used to facilitate collaboration and data sharing, which can speed up the process of digital transformation. By leveraging the power of connectivity, businesses can develop a range of products and services that can bring about a whole new level of efficiency, cost savings and customer satisfaction. This can be achieved by integrating data sources and creating better ways to monitor and manage the connected devices. 

Monitoring and analytics: IoT devices can be used to monitor and analyze data in real-time, providing valuable insights and helping to inform decisions and improve the decision-making process. This can help businesses identify trends, identify potential issues before they arise, and reduce downtime. It also provides a way to better understand customer behavior and gain valuable insights into customer preferences. With this data, businesses can tailor their products and services to better meet customer needs, resulting in improved customer loyalty and profitability.

Security: IoT solutions can provide additional layers of security to protect data and systems from potential threats. This can help to reduce the risk of data breaches and other malicious activities.  IoT solutions can also help to automate security-related processes and procedures. This can help to reduce the time and effort required to maintain a secure environment, allowing organizations to focus on other areas of their operations. Additionally, by having automated security, organizations can be sure that their security measures are consistently up-to-date and effective in protecting their data and systems.

Scalability: IoT solutions can be used to easily scale up or down resources to meet the changing needs of the organization. 

With the advent of the Internet of Things, Big Data is becoming more and more important. After all, when you have devices that are constantly collecting data, you need somewhere to store it all. But the Internet of Things is not just changing the way we store data; it’s changing the way we collect and use it as well. In this blog post, we will explore how the Internet of Things is transforming Big Data. From new data sources to new ways of analyzing data, the Internet of Things is changing the Big Data landscape in a big way.

How is the Internet of Things transforming Big Data?

The Internet of Things is transforming Big Data in a number of ways. One way is by making it possible to collect more data than ever before. This is because devices that are connected to the Internet can generate a huge amount of data. This data can be used to help businesses and organizations make better decisions.

Another way the Internet of Things is transforming Big Data is by making it easier to process and analyze this data. This is because there are now many tools and technologies that can help with this. One example is machine learning, which can be used to find patterns in data.

The Internet of Things is also changing the way we think about Big Data. This is because it’s not just about collecting large amounts of data – it’s also about understanding how this data can be used to improve our lives and businesses.

The Benefits of the Internet of Things for Big Data

1. The internet of things offers a number of benefits for big data.
2. It allows for a greater volume of data to be collected and stored.
3. Also, it provides a more diverse range of data types, which can be used to create more accurate and comprehensive models.
4. It enables real-time data collection and analysis, which can help organizations make better decisions and take action more quickly.
5. It can improve the accuracy of predictions by using historical data to train predictive models.
6. Finally, the internet of things can help reduce the cost of storing and processing big data.

The Challenges of the Internet of Things for Big Data

The internet of things is transforming big data in a number of ways. One challenge is the sheer volume of data that is generated by devices and sensors. Another challenge is the variety of data formats, which can make it difficult to derive insights. Additionally, the real-time nature of data from the internet of things presents challenges for traditional big data infrastructure.

Conclusion

The Internet of Things is bringing a new level of connectivity to the world, and with it, a huge influx of data. This data is transforming how businesses operate, giving them new insights into their customers and operations.

The Internet of Things is also changing how we interact with the world around us, making our lives more convenient and efficient. With so much potential, it's no wonder that the Internet of Things is one of the most talked-about topics in the tech world today.

The advent of the internet of things on Metaverse is expected to change its overall market outlook in the future. The IoT Includes a plethora of features which, in turn, will highly benefit the Metaverse Market in the upcoming years. With a growth rate of 38.25 per cent CAGR, the metaverse market size was estimated to be worth USD 124.04 billion in 2022 and USD 1655.29 billion in 2030.

The IoT, which was first launched in 1999, links hundreds of devices, including thermostats, voice-activated speakers, and medical equipment, to a variety of data. IoT is now poised to revolutionize the Metaverse as it effortlessly connects the 3D environment to a wide range of physical objects. One of the renowned & largest private software firms in the UK, IRIS Software Group, offers software solutions and services that significantly improve operational compliance, efficiency, and accuracy.

The identity environment will expand enormously as the Metaverse takes traction and new applications and access points emerge alongside it, creating additional entry points for potential bad market players. Already, 84% of corporate executives concur that their company now manages significantly more digital identities than it did ten years ago (up to 10x). Additionally, 95% of firms say they have trouble keeping track of all the identities that are currently a part of their organization (human and machine). We have a perfect storm of rising complexity and expanding threat vectors that may be exploited, which can lead to breaches, business disruption, and material expenses when we add in the Metaverse and the rise in IoT usage that will accompany it.

Top features of IoT:

 a.) A 360-degree enhanced and real-world training: 

Using the IoT, we are able to develop and test training methods in situations where we are unable to do so in the real world due to the scope and authenticity of training on extreme real-world situations (such as severe weather or cyber events) that can be done through virtual simulations using digital twins in the Metaverse. Io Train-sim will aid in preparing people and AI/software to cooperate to better recognize issues and lessen the impact in real life as virtual metaverse environments develop to more closely resemble reality.

b.) Smarter and better long-term planning along with its near-term response: 

The metaverse system will increasingly closely resemble our real world as it fills up with digital duplicates of real-world objects (such as cars, buildings, factories, and people). We will be able to run different long-term planning scenarios, identify the most optimal designs for our energy, transportation, and healthcare systems, and dynamically operate these techniques as the real world evolves thanks to this system-of-systems complicated virtual simulation (e.g., more renewable sources, new diseases, population migrations or demographic changes). These simulations will assist teams of humans in responding to current events and solving an issue utilizing monthly, weekly, or day-ahead planning, in addition to long-term planning. AI will then be used to learn from the outcome and enhance the response during the next event.

Conclusion

Brands are utilizing a variety of cutting-edge technologies to fuel the Metaverse with the aim of making the virtual as real-time and authentic as possible. These technologies include AR, VR, Blockchain, AI, and IoT. Sensors, cameras, and wearables are already implemented and in use due to the present IoT development. These gadgets are the engines that make it possible for the Metaverse to reflect the real world in real-time when they are connected to it. A metaverse representation of a physical site, such as Samsung's 837x recreation of its 837 Washington St. experience centre in New York City's Meatpacking District, might, for instance, be updated continuously and in real-time as objects enter and exit the physical location

Against the backdrop of digital technology and the industrial revolution, the Internet of Things has become the most influential and disruptive of all the latest technologies. As an advanced technology, IoT is showing a palpable difference in how businesses operate. 

Although the Fourth Industrial Revolution is still in its infancy, early adopters of this advanced technology are edging out the competition with their competitive advantage. 

Businesses eager to become a part of this disruptive technology are jostling against each other to implement IoT solutions. Yet, they are unaware of the steps in effective implementation and the challenges they might face during the process. 

This is a complete guide– the only one you’ll need – that focuses on delivering effective and uncomplicated IoT implementation. 

Key Elements of IoT

There are three main elements of IoT technology:

• Connectivity:

IoT devices are connected to the internet and have a URI – Unique Resource Identifier – that can relay data to the connected network. The devices can be connected among themselves to a centralized server, a cloud, or a network of servers.

• Data Communication:

IoT devices continuously share data with other devices in the network or the server. 

• Interaction

IoT devices do not simply gather data. They transmit it to their endpoints or server. There is no point in collecting data if it is not put to good use. The collected data is used to deliver IoT smart solutions in automation, take real-time business decisions, formulate strategies, or monitor processes. 

How Does IoT work?

IoT devices have URI and come with embedded sensors. With these sensors, the devices sense their environment and gather information. For example, the devices could be air conditioners, smart watches, cars, etc. Then, all the devices dump their collected data into the IoT platform or gateway. 

The IoT platform then performs analytics on the data from various sources and derives useful information per the requirement. 

What are the Layers in IoT Architecture?

Although there isn’t a standard IoT structure that’s universally accepted, the 4-layer architecture is considered to be the basic form. The four layers include perception, network, middleware, and application.

• Perception:

Perception is the first or the physical layer of IoT architecture. All the sensors, edge devices, and actuators gather useful information based on the project needs in this layer. The purpose of this layer is to gather data and transfer it to the next layer. 

• Network:

It is the connecting layer between perception and application. This layer gathers information from the perception and transmits the data to other devices or servers. 

• Middleware: 

The middleware layer offers storage and processing capabilities. It stores the incoming data and applies appropriate analytics based on requirements. 

• Application: 

The user interacts with the application layer, responsible for taking specific services to the end-user. 

Implementation Requirements

Effective and seamless implementation of IoT depends on specific tools, such as:

• High-Level Security 

Security is one of the fundamental IoT implementation requirements. Since the IoT devices gather real-time sensitive data about the environment, it is critical to put in place high-level security measures that ensure that sensitive information stays protected and confidential.  

• Asset Management

Asset management includes the software, hardware, and processes that ensure that the devices are registered, upgraded, secured, and well-managed. 

• Cloud Computing

Since massive amounts of structured and unstructured data are gathered and processed, it is stored in the cloud. The cloud acts as a centralized repository of resources that allows the data to be accessed easily. Cloud computing ensures seamless communication between various IoT devices. 

• Data Analytics

With advanced algorithms, large amounts of data are processed and analyzed from the cloud platform. As a result, you can derive trends based on the analytics, and corrective action can be taken. 

What are the IoT Implementation Steps?

Knowing the appropriate IoT implementation steps will help your business align your goals and expectations against the solution. You can also ensure the entire process is time-bound, cost-efficient, and satisfies all your business needs. 

Set Business Objectives 

IoT implementation should serve your business goals and objectives. Unfortunately, not every entrepreneur is an accomplished technician or computer-savvy. You can hire experts if you lack the practical know-how regarding IoT, the components needed, and specialist knowledge. 

Think of what you will accomplish with IoT, such as improving customer experience, eliminating operational inconsistencies, reducing costs, etc. With a clear understanding of IoT technology, you should be able to align your business needs to IoT applications. 

Hardware Components and Tools

Selecting the necessary tools, components, hardware, and software systems needed for the implementation is the next critical step. First, you must choose the tools and technology, keeping in mind connectivity and interoperability. 

You should also select the right IoT platform that acts as a centralized repository for collecting and controlling all aspects of the network and devices. You can choose to have a custom-made platform or get one from suppliers. 

Some of the major components you require for implementation include,

• Sensors
• Gateways
• Communication protocols
• IoT platforms
• Analytics and data management software

Implementation

Before initiating the implementation process, it is recommended that you put together a team of IoT experts and professionals with selected use case experience and knowledge. Make sure that the team comprises experts from operations and IT with a specific skill set in IoT. 

A typical team should be experts with skills in mechanical engineering, embedded system design, electrical and industrial design, technical expertise, and front/back-end development. 

Prototyping

Before giving the go-ahead, the team must develop an Internet of Things implementation prototype. 

A prototype will help you experiment and identify fault lines, connectivity, and compatibility issues. After testing the prototype, you can include modified design ideas. 

Integrate with Advanced technologies

After the sensors gather useful data, you can add layers of other technologies such as analytics, edge computing, and machine learning. 

The amount of unstructured data collected by the sensors far exceeds structured data. However, both structured and unstructured, machine learning, deep learning neural systems, and cognitive computing technologies can be used for improvement. 

Take Security Measures

Security is one of the top concerns of most businesses. With IoT depending predominantly on the internet for functioning, it is prone to security attacks. However, communication protocols, endpoint security, encryption, and access control management can minimize security breaches. 

Although there are no standardized IoT implementation steps, most projects follow these processes. But the exact sequence of IoT implementation depends on your project’s specific needs.

Challenges in IoT Implementation

Every new technology comes with its own set of implementation challenges. 

When you keep these challenges of IoT implementation in mind, you’ll be better equipped to handle them. 

• Lack of Network Security

When your entire system is dependent on the network connectivity for functioning, you are just adding another layer of security concern to deal with. 

Unless you have a robust network security system, you are bound to face issues such as hacking into the servers or devices. Unfortunately, the IoT hacking statistics are rising, with over 1.5 million security breaches reported in 2021 alone. 

• Data Retention and Storage 

IoT devices continually gather data, and over time the data becomes unwieldy to handle. Such massive amounts of data need high-capacity storage units and advanced IoT analytics technologies. 

• Lack of Compatibility 

IoT implementation involves several sensors, devices, and tools, and a successful implementation largely depends on the seamless integration between these systems. In addition, since there are no standards for devices or protocols, there could be major compatibility issues during implementation. 

IoT is the latest technology that is delivering promising results. Yet, similar to any technology, without proper implementation, your businesses can’t hope to leverage its immense benefits. 

Taking chances with IoT implementation is not a smart business move, as your productivity, security, customer experience, and future depend on proper and effective implementation. The only way to harness this technology would be to seek a reliable IoT app development company that can take your initiatives towards success.

How Doews IoT help in Retail? Continuous and seamless communication is now a reality between people, processes and things.  IoT has been enabling retailers to connect with people and businesses and gain useful insight about product performance and engagement of people with such products. 

Importance of IoT in Retail

• It helps improve customer experience in new ways and helps brick and mortar shops compete with their online counterparts by engaging customers in different ways.
• IoT can track customer preferences, analyze their habits and share relevant information with the marketing teams and help improve the product or brand features and design and keep the customer updated on new products, delivery status etc.
• Using IoT retailers can increase efficiency and profitability in various ways for their benefit.
• IoT can significantly improve the overall customer experience, like automated checkouts and integration with messaging platforms and order systems.
• It helps increase efficiency in transportation and logistics by reducing the time to deliver goods to market or store. It helps in vehicle management, and tracking deliveries. This helps in reducing costs, improving the bottom line and increasing customer satisfaction.
• Inventory management becomes easier with IoT. Tracking inventory is much easier and simpler from the stocking of goods to initiating a purchase.
• It helps increase operational efficiency in warehouses, by optimizing temperature controls, improving maintenance, and managing the warehouse. 

Use Cases of IoT in Retail

1. IoT is used in Facility management to ensure day-to-day areas are clean and can be used to monitor consumable supplies levels. It can be used to monitor store environments like temperature, lighting, ventilation and refrigeration. IoT can identify key areas that can provide a complete 360 degrees view of facility management.
2. It can help in tracking the number of persons entering a facility. This is especially useful because of the pandemic situation, to ensure that no overcrowding takes place.
   Occupancy sensors provide vital data on store traffic patterns and also on the time spent in any particular area. This helps retailers with better planning and product placement strategies. This helps in guided selling with more effective display setups, layouts, and space management.
3. IoT helps in a big way for Supply chain and logistics, by providing information on the stock levels. 
4. IoT helps in asset tracking in items like shopping carts and baskets. Sensors can ensure that location data is available for all carts making retrieval easy. It can help lock carts if they are taken out of location.
5. IoT devices can and are being used to personalize user experience. Bluetooth beacons are used to send personalized real-time alerts to phones when the customer is near an aisle or a store. This can prompt a customer to enter the store or look at the aisle area and take advantage of offers etc. IoT-based beacons, helps Target, collect user data and also send hyper-personalized content to customers.
6. Smart shelves are another example of innovative IoT ideas. Maintaining shelves to refill products or ensure correct items are placed on the right shelves is a time-consuming task. Smart shelves automate these tasks easily. They can help save time and resolve manual errors.

Businesses should utilize new technologies to revolutionize the retail sector in a better way. Digitalization or digital transformation of brick and mortar stores is not a new concept. With every industry wanting to improve its services and facilities and trying to stay ahead of the competition, digitalization in retail industry is playing a big role in this transformation. To summarize, digitalization helps in enhanced data collection, helps data-driven customer insights, gives a better customer experience, and increases profits and productivity. It encourages a digital culture.

Arm DevSummit 2020 debuted this week (October 6 – 8) as an online virtual conference focused on engineers and providing them with insights into the Arm ecosystem. The summit lasted three days over which Arm painted an interesting technology story about the current and future state of computing and where developers fit within that story. I’ve been attending Arm Techcon for more than half a decade now (which has become Arm DevSummit) and as I perused content, there were several take-a-ways I noticed for developers working on microcontroller based embedded systems. In this post, we will examine these key take-a-ways and I’ll point you to some of the sessions that I also think may pique your interest.

(For those of you that aren’t yet aware, you can register up until October 21^st (for free) and still watch the conferences materials up until November 28th . Click here to register)

Take-A-Way #1 – Expect Big Things from NVIDIAs Acquisition of Arm

As many readers probably already know, NVIDIA is in the process of acquiring Arm. This acquisition has the potential to be one of the focal points that I think will lead to a technological revolution in computing technologies, particularly around artificial intelligence but that will also impact nearly every embedded system at the edge and beyond. While many of us have probably wondered what plans NVIDIA CEO Jensen Huang may have for Arm, the Keynotes for October 6^th include a fireside chat between Jensen Huang and Arm CEO Simon Segars. Listening to this conversation is well worth the time and will help give developers some insights into the future but also assurances that the Arm business model will not be dramatically upended.

Take-A-Way #2 – Machine Learning for MCU’s is Accelerating

It is sometimes difficult at a conference to get a feel for what is real and what is a little more smoke and mirrors. Sometimes, announcements are real, but they just take several years to filter their way into the market and affect how developers build systems. Machine learning is one of those technologies that I find there is a lot of interest around but that developers also aren’t quite sure what to do with yet, at least in the microcontroller space. When we hear machine learning, we think artificial intelligence, big datasets and more processing power than will fit on an MCU.

There were several interesting talks at DevSummit around machine learning such as:

• Beyond ML – A Neuromorphic Approach to AI by Paul Isaacs
• tinyML Development with TensorFlow Lite for Microcontrollers and CMSIS-NN by Peter Warden and Fredrik Knutsson
• uTVM, an AI Compiler for Arm Microcontrollers by Thomas Gall
• Machine Learning Made Possible for Embedded Developers with Zero AI Skills by Francois de Rochebouet

Some of these were foundational, providing embedded developers with the fundamentals to get started while others provided hands-on explorations of machine learning with development boards. The take-a-way that I gather here is that the effort to bring machine learning capabilities to microcontrollers so that they can be leveraged in industry use cases is accelerating. Lots of effort is being placed in ML algorithms, tools, frameworks and even the hardware. There were several talks that mentioned Arm’s Cortex-M55 architecture that will include Helium technology to help accelerate machine learning and DSP processing capabilities.

Take-A-Way #3 – The Constant Need for Reinvention

In my last take-a-way, I eluded to the fact that things are accelerating. Acceleration is not just happening though in the technologies that we use to build systems. The very application domain that we can apply these technology domains to is dramatically expanding. Not only can we start to deploy security and ML technologies at the edge but in domains such as space and medical systems. There were several interesting talks about how technologies are being used around the world to solve interesting and unique problems such as protecting vulnerable ecosystems, mapping the sea floor, fighting against diseases and so much more.

By carefully watching and listening, you’ll notice that many speakers have been involved in many different types of products over their careers and that they are constantly having to reinvent their skill sets, capabilities and even their interests! This is what makes working in embedded systems so interesting! It is constantly changing and evolving and as engineers we don’t get to sit idly behind a desk. Just as Arm, NVIDIA and many of the other ecosystem partners and speakers show us, technology is rapidly changing but so are the problem domains that we can apply these technologies to.

Take-A-Way #4 – Mbed and Keil are Evolving

There are also interesting changes coming to the Arm toolchains and tools like Mbed and Keil MDK. In Reinhard Keil’s talk, “Introduction to an Open Approach for Low-Power IoT Development“, developers got an insight into the changes that are coming to Mbed and Keil with the core focus being on IoT development. The talk focused on the endpoint and discussed how Mbed and Keil MDK are being moved to an online platform designed to help developers move through the product development faster from prototyping to production. The Keil Studio Online is currently in early access and will be released early next year.

(If you are interested in endpoints and AI, you might also want to check-out this article on “How Do We Accelerate Endpoint AI Innovation? Put Developers First“)

Conclusions

Arm DevSummit had a lot to offer developers this year and without the need to travel to California to participate. (Although I greatly missed catching up with friends and colleagues in person). If you haven’t already, I would recommend checking out the DevSummit and watching a few of the talks I mentioned. There certainly were a lot more talks and I’m still in the process of sifting through everything. Hopefully there will be a few sessions that will inspire you and give you a feel for where the industry is headed and how you will need to pivot your own skills in the coming years.

Originaly posted here

In a recent issue of IEEE Spectrum, Mikhail Dyakonov makes a pretty compelling argument that quantum computing (QC) isn't going to fly anytime soon. Now, I'm no expert on QC, and there sure is a lot of money being thrown at the problem by some very smart people, but having watched from the sidelines QC seems a lot like fusion research. Every year more claims are made, more venture capital gets burned, but we don't seem to get closer to useful systems.

Consider D-Wave Systems. They've been trying to build a QC for twenty years, and indeed do have products more or less on the market, including, it's claimed, one of 1024 q-bits. But there's a lot of controversy about whether their machines are either quantum computers at all, or if they offer any speedup over classical machines. One would think that if a 1K q-bit machine really did work the press would be all abuzz, and we'd be hearing constantly of new incredible results. Instead, the machines seem to disappear into research labs.

Mr. Duakonov notes that optimistic people expect useful QCs in the next 5-10 years; those less sanguine expect 20-30 years, a prediction that hasn't changed in two decades. He thinks a window of many decades to never is more realistic. Experts think that a useful machine, one that can do the sort of calculations your laptop is capable of, will require between 1000 and 100,000 q-bits. To me, this level of uncertainty suggests that there is a profound lack of knowledge about how these machines will work and what they will be able to do.

According to the author, a 1000 q-bit machine can be in 2¹⁰⁰⁰ states (a classical machine with N transistors can be in only 2^N states), which is about 10³⁰⁰, or more than the number of sub-atomic particles in the universe. At 100,000 q-bits we're talking 10^30,000, a mind-boggling number.

Because of noise, expect errors. Some theorize that those errors can be eliminated by adding q-bits, on the order of 1000 to 100,000 additional per q-bit. So a useful machine will need at least millions, or perhaps many orders of magnitude more, of these squirrelly microdots that are tamed only by keeping them at 10 millikelvin.

A related article in Spectrum mentions a committee formed of prestigious researchers tasked with assessing the probability of success with QC concluded that:

"[I]t is highly unexpected" that anyone will be able to build a quantum computer that could compromise public-key cryptosystems (a task that quantum computers are, in theory, especially suitable for tackling) in the coming decade. And while less-capable "noisy intermediate-scale quantum computers" will be built within that time frame, "there are at present no known algorithms/applications that could make effective use of this class of machine," the committee says."

I don't have a dog in this fight, but am relieved that useful QC seems to be no closer than The Distant Shore (to quote Jan de Hartog, one of my favorite writers). If it were feasible to easily break encryption schemes banking and other systems could collapse. I imagine Blockchain would fail as hash algorithms became reversable. The resulting disruption would not be healthy for our society.

On the other hand, Bruce Schneier's article in the March issue of IEEE Computing Edge suggests that QC won't break all forms of encryption, though he does think a lot of our current infrastructure will be vulnerable. The moral: if and when QC becomes practical, expect chaos.

I was once afraid of quantum computing, as it involves mechanisms that I'll never understand. But then I realized those machines will have an API. Just as one doesn't need to know how a computer works to program in Python, we'll be insulated from the quantum horrors by layers of abstraction.

Originaly posted here

SSE Airtricity employees Derek Conty, left, Francie Byrne, middle, and Ryan Doran, right, install solar panels on the roof of Kinsale Community School in Kinsale, Ireland. The installation is part of a project with Microsoft to demonstrate the feasibility of distributed power purchase agreements. Credit: Naoise Culhane

by John Roach

Solar panels being installed on the roofs of dozens of schools throughout Dublin, Ireland, reflect a novel front in the fight against global climate change, according to a senior software engineer and a sustainability lead at Microsoft.

The technology copmpany partnered with SSE Airtricity, Ireland's largest provider of 100% green energy and a part of FTSE listed SSE Group, to install and manage the internet-connected solar panels, which are connected via Azure IoT to Microsoft Azure, a cloud computing platform.

The software tools aggregate and analyze real-time data on energy generated by the solar panels, demonstrating a mechanism for Microsoft and other corporations to achieve sustainability goals and reduce the carbon footprint of the electric power grid.

"We need to decarbonize the global economy to avoid catastrophic climate change," said Conor Kelly, the software engineer who is leading the distributed solar energy project for Microsoft Azure IoT. "The first thing we can do, and the easiest thing we can do, is focus on electricity."

Microsoft's $1.1 million contribution to the project builds on the company's ongoing investment in renewable energy technologies to offset carbon emissions from the operation of its datacenters.

A typical approach to power datacenters with renewable energy is for companies such as Microsoft to sign so-called power purchase agreements with energy companies.The agreements provide financial guarantees needed to build industrial-scale wind and solar farms and connections to the power grid.

The new project demonstrates the feasibility of agreements to install solar panels on rooftops distributed across towns with existing grid connections and use internet of things, or IoT, technologies to aggregate the accumulated energy production for carbon offset accounting.

"It utilizes existing assets that are sitting there unmonetized, which are roofs of buildings that absorb sunlight all day," Kelly said.

New Business Model

The project is also a proof-of-concept, or blueprint, for how energy providers can adapt as the falling price of solar panels enables distributed electric power generation throughout the existing electric power grid.

Traditionally, suppliers purchase power from central power plants and industrial-scale wind and solar farms and sell it to consumers on the distribution grid. Now, energy providers like SSE Airtricity provide renewable energy solutions that allow end consumers to generate power, from sustainable sources, using the existing grid connection on their premises.

"The more forward-thinking energy providers that we are working with, like SSE Airtricity, identify this as an opportunity and industry changing shift in how energy will be generated and consumed," Kelly noted.

The opportunity comes in the ability to finance the installation of solar panels and batteries at homes, schools, businesses and other buildings throughout a community and leverage IoT technology to efficiently perform a range of services from energy trading to carbon offset accounting.

Kelly and his team with Azure IoT are working with SSE Airtricity to develop the tools and machine learning models necessary to unlock this opportunity.

"Instead of having utility scale solar farms located outside of cities, you could have a solar farm at the distribution level, spread across a number of locations," said Fergal Ahern, a business energy solutions manager and renewable energy expert with SSE Airtricity.

For the distributed power purchase agreement, SSE Airtricity uses Azure IoT to aggregate the generation of all the solar panels installed across 27 schools around the provinces of Leinster, Munster and Connacht and run it through a machine learning model to determine the carbon emissions that the solar panels avoid.

The schools use the electricity generated by the solar panels, which reduces their utility bills; Microsoft receives the renewable energy credits for the generated electricity, which the company applies to its carbon neutrality commitments.

The panels are expected to produce enough energy annually to power the equivalent of 68 Irish homes for a year and abate more than 2.1 million kilograms, which is equivalent to 4.6 million pounds, of carbon dioxide emissions over the 15 years of the agreement, according to Kelly.

"This is additional renewable energy that wouldn't have otherwise happened," he said. "Every little bit counts when it comes to meeting our sustainability targets and combatting climate change."

Every little bit counts

Victory Luke, a 16 year old student at Collinstown Park Community College in Dublin, has lived by the "every little bit counts" mantra since she participated in a "Generation Green" sustainability workshop in 2019 organized by the Sustainable Energy Authority of Ireland, SSE Airtricity and Microsoft.

The workshop was part of an education program surrounding the installation of solar panels and batteries at her school along with a retrofit of the lighting system with LEDs. Digital screens show the school's energy use in real time, allowing students to see the impact of the energy efficiency upgrades.

Luke said the workshop captured her interest on climate change issues. She started reading more about sustainability and environmental conservation and agreed to share her newfound knowledge with the younger students at her school.

"I was going around and talking to them about energy efficiency, sharing tips and tricks like if you are going to boil a kettle, only boil as much water as you need, not too much," she explained.

That June, the Sustainable Energy Authority of Ireland invited her to give a speech at the Global Conference on Energy Efficiency in Dublin, which was organized by the International Energy Agency, an organization that works with governments and industry to shape sustainable energy policy.

"It kind of felt surreal because I honestly felt like I wasn't adequate enough to be speaking about these things," she said, noting that the conference attendees included government ministers, CEOs and energy experts from around the world.

At the time, she added, the global climate strike movement and its youth leaders were making international headlines, which made her advocacy at school feel even smaller. "Then I kind of realized that it is those smaller things that make the big difference," she said.

An edge device is the network component that is responsible for connecting a local area network to an external or wide area network, which can be accessed from anywhere. Edge devices offer several new services and improved outcomes for IoT deployments across all markets. Smart services that rely on high volumes of data and local analysis can be deployed in a wide range of environments.

Edge device provides the local data to an external network. If protocols are different in local and external networks, it also translates this information, and make the connection between both network boundaries. Edge devices analyze diagnostics and automatic data populating; however, it is necessary to make a secure connection between the field network and cloud computing. In the event of loss of internet connection or cloud crash edge device will store data until the connection is established, so it won’t lose any process information. The local data storage is optional and not all edge devices offer local storage, it depends on the application and service required to implement on the plant.

How does an edge device work?

An edge device has a very straightforward working principle, it communicates between two different networks and translates one protocol into another. Furthermore, it creates a secure connection with the cloud.

An edge device can be configured via local access and internet or cloud. In general, we can say an edge device is a plug-and-play, its setup is simple and does not require much time to configure.

Why should I use an edge device?

Depending on the service required in the plant, the edge devices will be a crucial point to collect the information and create an automatic digital twin of your device in the cloud. 

Edge devices are an essential part of IoT solutions since they connect the information from a network to a cloud solution. They do not affect the network but only collect the data from it, and never cause a problem with the communication between the control system and the field devices. by using an edge device to collect information, the user won’t need to touch the control system. Edge is one-way communication, nothing is written into the network, and data are acquired with the highest possible security.

Edge device requirements

Edge devices are required to meet certain requirements that are to meet at all conditions to perform in different secretions. This may include storage, network, and latency, etc.

Low latency

Sensor data is collected in near real-time by an edge server. For services like image recognition and visual monitoring, edge servers are located in very close proximity to the device, meeting low latency requirements. Edge deployment needs to ensure that these services are not lost through poor development practice or inadequate processing resources at the edge. Maintaining data quality and security at the edge whilst enabling low latency is a challenge that need to address.

Network independence

IoT services do not care for data communication topology.  The user requires the data through the most effective means possible which in many cases will be mobile networks, but in some scenarios, Wi-Fi or local mesh networking may be the most effective mechanism of collecting data to ensure latency requirements can be met.

Data security

Users require data at the edge to be kept secure as when it is stored and used elsewhere. These challenges need to meet due to the larger vector and scope for attacks at the edge. Data authentication and user access are as important at the edge as it is on the device or at the core.  Additionally, the physical security of edge infrastructure needs to be considered, as it is likely to hold in less secure environments than dedicated data centers.

Data Quality

Data quality at the edge is a key requirement to guarantee to operate in demanding environments. To maintain data quality at the edge, applications must ensure that data is authenticated, replicated as and assigned into the correct classes and types of data category.

Flexibility in future enhancements

Additional sensors can be added and managed at the edge as requirements change. Sensors such as accelerometers, cameras, and GPS, can be added to equipment, with seamless integration and control at the edge.

Local storage

Local storage is essential in the event of loss of internet connection or cloud crash edge device will store data until the connection is established, so it won’t lose any process information. The local data storage is optional and not all edge devices offer local storage, it depends on the application and service required to implement on the plant

Originaly Posted here

by Singapore University of Technology and Design

Internet-of-Things (IoT) such as smart home locks and medical devices, depend largely on Bluetooth low energy (BLE) technology to function and connect across other devices with reduced energy consumption. As these devices get more prevalent with increasing levels of connectivity, the need for strengthened security in IoT has also become vital.

A research team, led by Assistant Professor Sudipta Chattopadhyay from the Singapore University of Technology and Design (SUTD), wit team members from SUTD and the Institute for Infocomm Research (I2R), designed and implemented the Greyhound framework, a tool used to discover SweynTooth—a critical set of 11 cyber vulnerabilities.

Their study was presented at the USENIX Annual Technical Conference (USENIX ATC) on 15 to 17 July 2020 and they have been invited to present at the upcoming Singapore International Cyber Week (SICW) in October 2020.

These security lapses were found to affect devices by causing them to crash, reboot or bypass security features. At least 12 BLE based devices from eight vendors were affected, including a few hundred types of IoT products including pacemakers, wearable fitness trackers and home security locks.

The SweynTooth code has since been made available to the public and several IoT product manufacturers have used it to find security issues in their products. In Singapore alone, 32 medical devices reported to be affected by SweynTooth and 90% of these device manufacturers have since implemented preventive measures against this set of cyber vulnerabilities.

Regulatory agencies including the Cyber Security Agency and the Health Sciences Authority in Singapore as well as the Department of Homeland Security and the Food and Drug Administration in the United States have reached out to the research team to further understand the impact of these vulnerabilities.

These agencies have also raised public alerts to inform medical device manufacturers, healthcare institutions and end users on the potential security breach and disruptions. The research team continues to keep them updated on their research findings and assessments.

Beyond Bluetooth technology, the research team designed the Greyhound framework using a modular approach so that it could easily be adapted for new wireless protocols. This allowed the team to test it across the diverse set of protocols that IoTs frequently employ. This automated framework also paves new avenues in the testing security of more complex protocols and IoTs in next-generation wireless protocol implementations such as 5G and NarrowBand-IoT which require rigorous and systematic security testing.

"As we are transitioning towards a smart nation, more of such vulnerabilities could appear in the future. We need to start rethinking the device manufacturing design process so that there is limited reliance on communication modules such as Bluetooth to ensure a better and more secure smart nation by design," explained principal investigator Assistant Professor Sudipta from SUTD.

Originally posted HERE.

When you’re in technology, you have to expect change. Yet, there’s something to the phrase “the more things change, the more they stay the same.” For instance, I see in the industrial internet of things (IIoT) a realm that’ll dramatically shape the future - how we manufacture, the way we run our factories, workforce needs – but the underlying business goals are the same as always.

Simply put, while industrial enterprise initiatives may change, financial objectives don’t – and they’re still what matter most. That’s why IIoT is so appealing. While the possibilities of smart and connected operations, sites and products certainly appeal to the dreamer and innovator, the clear payoff ensures that it’s a road even the most pragmatic decision-maker will eagerly follow.

The big three
When it comes to industrial enterprises, IIoT addresses the “big three” financial objectives head on. The technology maximizes revenue growth, reduces operating expense and increases asset efficiency.

IIoT does this in numerous ways. It yields invaluable operational intelligence, like real-time performance management data, to reduce manufacturing costs, increase flexibility and enable agility. When it comes to productivity, connected digital assets can empower a workforce with actionable insights to improve productivity and quality, even prevent safety and compliance issues.

For example, recognizing defects in a product early on can save time, materials, staff hours and possibly even a company’s reputation.

Whether on or off the factory floor, IIoT can be used to optimize asset efficiency. With real-time monitoring, diagnostics and analytics, downtime can be reduced or avoided. Asset utilization can also be evaluated and maximized. Think applications like equipment health monitoring, predictive maintenance, the ability to provide augmented 3D instructions for complex repairs. And, you can also scale production more precisely via better control over processes and inventory.

All of this accelerates time to market; another key benefit of IIoT and long held business goal.

Why is 5G important for IIoT and augmented reality (AR)?
As we look at the growing need to connect more devices, more sensors and install things like real-time cameras for doing analytics, there is growing stress and strain that is brought into industrial settings. We have seen the need to increase connectivity while having greater scalability, performance, accessibility, reliability, and broader reach with a lower cost of ownership become much more important. This is where 5G can make a real difference.

Many of our customers have seen what we are doing with augmented reality and the way that PTC can help operators service equipment. But in the not so distant future, the way that people interact with robotics, for example, will change. There will be real-time video to do spatial analytics on the way that people are working with man and machines and we’ll be able to unlock a new level of intelligence with a new layer of connectivity that helps drive better business outcomes.

Partner up
It sounds nice but the truth is, a lot of heavy lifting is required to do IIoT right. The last thing you want to do is venture into a pilot, run into problems, and leave the C-suite less than enthused with the outcome. And make no mistake, there’s a lot potential pitfalls to be aware of.

For instance, lengthy proof of concept periods, cumbersome processes and integrations can slow time to market. Multiple, local integrations can be required when connectivity and device management gets siloed. If not done right, you may only gain limited visibility into devices and the experience will fall short. And, naturally, global initiatives can be hindered by high roaming costs and deployment obstacles.

That said, you want to harness best of breed providers, not only to realize the full benefits of Industry 4.0, but to set yourself up with a foundation that’ll be able to harness 5G developments. You need a trusted IoT partner, and because of the sophistication and complexity, it takes an ecosystem of proven innovators working collaboratively.

That’s why PTC and Ericsson are partners.

Doing what’s best
Ericsson unlocks the full value of global cellular IoT connectivity and provides on-premise solutions. PTC offers an industrial IoT platform that’s ready to configure and deploy, with flexible connectivity and capabilities to build solutions without manual coding.

Drilling down a bit further, Ericsson’s IoT Accelerator can connect and manage billions of devices and millions of applications easily, seamlessly and globally. PTC’s IoT solutions digitalize processes and products, combining the physical and digital worlds seamlessly.

And with wireless connectivity, we can deploy a lot of new technology – from augmented reality to artificial intelligence applications – without having to think about the time and cost of creating fixed infrastructures, running wires, adding network capacity and more.

According ABI Research, organizations that embrace Industry 4.0 and private cellular have the potential to improve gross margins by 5-13% in factory and warehouse operations. Manufacturers can expect a 10x return on their investment. And with 4.3 billion wireless connections in smart factories anticipated by 2030, it’s clear where things are headed.

By focusing on what we each do best, PTC and Ericsson is able to do what’s best for our customers. We can help them build and scale global cellular IoT deployments faster and gain a competitive advantage. They can reap the advantages of Industry 4.0 and create that path to 5G, future-proofing their operations and enjoying such differentiators as network slicing, edge computing and high-reliability, low latency communications.

Further, with our histories of innovation, customers are assured they’ll be supported in the future, remaining out front with the ability to adapt to change, grow and deliver on financial objections.

Editor's Note: This post was originally published by Steve Dertien, Chief Technology Officer for PTC, on Ericsson's website, and is part of a joint content effort with Kiva Allgood, head of IoT for Ericsson. To view Steve's original, please click here. To read Kiva's complementary post, please click here.