Industrial IoT, IoT Security
Article | July 12, 2023
2022 looks bright for power optimization! The vibrant research and development in Internet of Things (IoT) is fueling the expansion of wireless monitoring solutions and enabling giant leaps in terms of low-power design. A longer lifetime for your batteries, and thus for your device, is a dream about to come true.
We have gathered some of the most notable power optimization trends that are getting us all excited for 2022…
5G, the next era of broadband cellular networks will offer improved power saving capabilities
The next wave of wider 5G cellular technology is designed to support various new highly challenging industrial use cases. These usually require increased hardware complexity and more processing, together with higher processing power. These requirements can raise power consumption quite significantly.
Smart power consumption and energy efficiency are thus becoming keys for the success of these applications and 5G technology.To that extent, 5G New Radio (NR) has progressed swiftly. The new 3GPP™ release is designed to significantly improve the performance, flexibility, scalability, and efficiency of current mobile networks. Improved power saving features now allow IoT developers to get the most out of the available battery capacity. This could make all the difference for new IoT use cases and efficiencies.
A new generation of sensors are optimized for low power technologies
New families of ‘breakthrough’ sensors, based on anultra-low power architectureare optimized for use in compact wireless devices. These sensors offer a richer set of functionalities and can be combined to create new insights (sensor fusion). One of the greatest challenges facing developers of these small form-devices is power consumption. Aware of these limitations, hardware manufacturers have been working hard to address them. Integrated circuit designs and techniques are now using less power while smart processing capabilities are enabling the sensors to intelligently manage sensing functionalities,delivering ultra-low power performance for best-in-class power consumption. The use of advanced Low Energy Bluetooth and wireless protocols (e.g. Bluetooth Low Energy (BLE) or ZigBee Green Power) also allows the transmission of data to the gateway more efficiently compared to prior solutions, opening new possibilities for developers.
Big Data, Analytics, Machine Learning and Edge computing are picking up the pace
The explosion in data volume and diversity is forcing organizations to rethink the way they process the information. Indeed, capturing, sending and processing the information in the cloud can be taxing for the network, the storage and the computing infrastructures which demands more processing power, hence the need to keep the transmission window as short as possible.
This has led to the development of advanced devices capable of collecting, processing and storing data autonomously before the data is sent to the servers. This concept is calledEdge computing. By reducing the need for data to be streamed through the networks, diminishing computing and processing costs,Edge computing contributes to optimizing power performance, whilst delivering quality data in a more sustainable way.
The rise of DevOps and new IoT Device Management platforms are contributing to better efficiency and better devices
The rise ofDevOpshas been swift. Derived from Development and Operations, ‘DevOps’ teams are responsible for making sure that the infrastructure is being maintained properly.With the help of IoT Device Management platforms—which are a central part of today’s IoT ecosystems— DevOps teams can better manage, scale and operate their fleet of devices remotely and reduce long-term operational costs.One of the areas that benefits from the rise of DevOps implementation is power supply optimization, as more efficient protocols such as Lightweight Machine to Machine (LwM2M) allow for device and battery monitoring, remote device actions and faster communication.
Harvesting technologies are becoming more effective
Power harvesting technologies include processes where energy from ambient sources such as the sun, temperature, movement or wind, is captured and stored to power wireless autonomous devices. Now gaining experience,harvesting technologies can exploit natural resources better than ever before.
As a result,the gap between the power requirements of embedded systems and the energy generated by energy harvesting systems is finally closing. Industrial applications for these technologies are still very limited, but coupled to efficient rechargeable batteries, they can present new opportunities for devices deployed in wild remote areas.
Power optimization tools are becoming increasingly exhaustive and reliable
Battery optimization is everyone's business and needs to be considered throughout the overall system performance analysis, from prototyping to deployment and on toward maintenance cycles.
Several innovating tools haveappeared on the market over the past few years and developers have now access toa rich ecosystem of tools to analyze their overall system performance.
Wisebatt for Saft for example can help creating a virtual prototype and simulate its consumption.Deutsche Telekom’s IoT Solution Optimizergoes even further. You can model the complete system to identify potential energy consumption issues or leaks. The system can not only recommend the right combination of power saving features based on your use case, but also can help you visualize how communication payload size, protocol use and communication frequency impact your battery life.
When at the prototype stage,Qoitec Otii solution measures in real time the consumption of your device at various temperatures, up to the measurement of the firmware and hardware operations without the need for expensive testing. These tools are constantly enhanced and improved to deliver better analysis and more accurate data.
With an increased awareness from IoT developers of the stakes of power consumption and the growing rate of low-power innovations, batteries are now able to outlive the devices they’re in. This opens the doors tomany new markets and applications and above all to more sustainable consumption patterns. When we told you the future looks bright, we weren’t joking!
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IoT Security
Article | June 27, 2023
The evolution of internet-based market models has changed the way businesses operate. Present-day businesses know that data visualization in business intelligence is integral to competitive success. Therefore, businesses are now expanding their data and intelligence retrieval capacities. As a result, IoT (Internet of Things) data visualization is gaining popularity among industrialists and researchers across various disciplines.
In corporate finance, IoT-based efficient data visualization analyses data from multiple sources with the help of corporate analytics management tools and manages data quality for business intelligence to reduce the risk of leaks.
Impact of IoT Data Visualization on Corporate Finance BI
Data is everywhere— right from a customer's first visit to your company’s website until he signs out, all the behavioral patterns and data are tracked. All this data becomes useless unless it is utilized for a particular purpose.
Analyzing this data to predict future trends is one of the significant benefits of smart data visualization tools and technologies. It helps to slice and dice the data gained from different sources of different complexity levels to the minute granular level. Business intelligence utilizes these insights and the existing database to run risk analysis.
It gives an overview of your financial performance and the risks and exposures it faces. And if you switch the KPIs at the center of any dashboard, your entire team can instantly access the most important and relevant data.
IoT data visualization can measure big data on customers more efficiently, allowing organizations to add value to their customers. Customized tools will analyze your customers’ data and produce reports according to specific customer needs to help you get a deeper insight. Corporations can also utilize this data to better understand their competitors’ benchmarks.
Customizable IoT Data to Store Millions of Data Points in One Place
IoT collects millions of data from various complex sources. The data visualization dashboard contains multiple widgets that convert this data into various forms, such as line graphs, geographical maps, bar charts, pie charts, gauges, heat maps, etc.
This information, transmitted into multiple visualizations, helps organizations to unlock every piece of data into a valuable asset.
The Benefits of Using IoT Data Visualization
Businesses can collect, analyze and monitor a variety of data using IoT, such as internet usage data, video surveillance data, mobile app usage, and social media. It helps businesses to design products and provide personalized value-added services to drive better consumer engagement. Here are some key benefits IoT data visualization offers:
Unlock multiple insights across various verticals
Addressing important financial concerns proactively
Combination of multiple data sources into a single insightful dashboard
Multi-layered visual data.
Combines new data with the existing data to analyze new business opportunities.
Better performance on IoT data flow.
Analyze multiple data correlations in real-time
Improved Collaboration
Well-coordinated and efficient performance.
Cost reduction
Accurate data interpretation
Mitigate risk factor
Better decision making
Conclusion
Hands down, IoT data visualization intelligence in a company’s business operations will lead to better decision-making. But, before you choose an IoT data visualization tool for your business, you should know what kind of data you need to analyze and if you need any additional historical data. Because IoT services offer data visualization tools and techniques to analyze and monitor the data accordingly to predict future trends. So, it’s important to identify the goals before selecting a tool for your organization.
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Enterprise Iot
Article | May 11, 2023
5G trends are shaping the future of various technologies, from the Internet of Things to virtual reality. Learn more about the top trends in 5G to stay ahead of the competition in this sector.
Contents
1 The Current State of IoT Data Security
2 Top Trends in IoT Data Security in 2023
2.1 Emergence of AI-powered Security Solutions
2.2 Potential of Blockchain Technology
2.3 Growing Use of Zero-trust Security Frameworks
2.4 Greater Emphasis on End-to-end Encryption
2.5 Industry and Government Collaboration
3 Conclusion
As the Internet of Things (IoT) continues to rapidly expand, data security has become a critical concern for businesses and consumers alike. With recent high-profile breaches and cyberattacks, the latest trends in IoT data security focus on implementing stronger encryption and authentication protocols, as well as enhancing device-level security measures to protect sensitive data from potential threats.
1 The Current State of IoT Data Security
The growing adoption of IoT has led to a digital transformation in the way businesses operate. IoT technology has enabled organizations to collect and analyze vast amounts of data in real-time, allowing for improved decision-making, increased operational efficiency, and enhanced customer experiences. Despite these benefits, organizations are currently facing significant IoT data security challenges that must be addressed to fully realize the potential of this technology.
Companies recognize unauthorized access (43%), data privacy (38%), and data integrity (31%) as top IoT security challenges.
(Source: Statista)
Businesses are actively addressing these security challenges by investing in IoT and data security solutions. The global market for IoT data security continues to grow, and companies are increasingly investing in strategies for data security in the IoT. To secure access to mission-critical connected devices and sensitive data, it is imperative for businesses to keep track of IoT trends in data security.
2 Top Trends in IoT Data Security in 2023
2.1 Emergence of AI-powered Security Solutions
AI-powered security systems can rapidly detect and respond to attacks, reducing the likelihood of significant damage to IoT devices or networks. In particular, its ability to analyze vast amounts of data in real-time and identify anomalies or potential security threats makes AI a vital component of an IoT data security strategy.
Detecting an IoT security breach in progress is possible with AI security systems, which identifies unusual behavior by analyzing data patterns from IoT devices. AI can also be used to diagnose potential vulnerabilities in IoT devices and networks, allowing organizations to take proactive measures to address them before they are exploited.
The pattern recognition capabilities of AI also help secure IoT technology through predictive analytics. By analyzing past data breaches and attacks, AI systems detect potential cyberattacks and develop predictive models to detect and respond to them proactively.
AI-driven security systems have the potential to streamline incident response by lessening the load on cybersecurity teams and reducing response time. The ability to adapt and learn from a previous cyberattack allows machine learning (ML) algorithms to create novel strategies that prevent similar attacks in the future.
AI represents a significant development in addressing IoT security concerns since it provides sophisticated capabilities to protect IoT networks and devices that conventional security measures cannot provide. AI-enabled security systems deliver immediate identification, reaction, and deterrence of possible threats, which is why they will be critical in ensuring data security in the IoT.
2.2 Potential of Blockchain Technology
Blockchain's unique features, such as decentralization, immutability, and cryptographic security, provide a robust framework for secure communication and data sharing among IoT devices. By leveraging blockchain technology, businesses can ensure their IoT data's integrity, confidentiality, and authenticity.
One of the key advantages of using blockchain for IoT data security is its decentralized nature. Blockchain networks are distributed and run on a peer-to-peer basis, making it difficult for attackers to compromise the network. This also makes it an ideal solution for recording and securing data from multiple access points, such as IIoT systems.
Additionally, blockchain networks are designed to be immutable, making them an ideal solution for IoT data security and providing a tamper-proof and transparent ledger for recording data flow. This can help enterprises identify and mitigate security threats more quickly and efficiently, reducing the risk of cybersecurity incidents. A research paper published in Wireless Networks highlights the advantage of using a Blowfish Blockchain Model to enable IoT data sharing security, particularly for multimedia content.
Blockchain technology is a promising solution for securing IoT data. Its unique features, including decentralization, immutability, and cryptographic security, make it an ideal candidate for many IoT use cases. This technology can potentially transform data security for IoT devices by offering the IoT sector the solution it requires.
2.3 Growing Use of Zero-trust Security Frameworks
Zero-trust frameworks ensure that only authorized devices and users can access sensitive data and systems, protecting against insider threats and external attacks. This is especially important in IoT environments, where devices may lack traditional security measures like firewalls and antivirus software.
Device identity management is a critical component of zero-trust security for IoT data. Only recognized devices are allowed access to a network or data by leveraging processes and technologies that authenticate device identity. With Zero Trust, any connected device must be authorized before accessing any resources, including data.
By closely monitoring and managing access, businesses can maintain the security of the IoT. This protects against threats that exploit weak device identity management. Overall, zero-trust security frameworks are essential for safeguarding IoT data from malicious actors and protecting the integrity of IoT ecosystems.
2.4 Greater Emphasis on End-to-end Encryption
IoT poses a threat to data security when users do not take proper measures to protect the data generated. End-to-end encryption provides a strong layer of protection against unauthorized access, interception, and other cyber threats by encrypting data at the source, during transmission, and at rest.
IoT devices collect and process a wide range of sensitive data, from personal information and financial data to critical infrastructure and medical records. This data is often transmitted over networks and shared with cloud services, and the risk of cyberattacks during transmission cannot be ignored.
End-to-end encryption can provide a strong layer of protection by encrypting data at the source, working to improve the limited data security of the IoT. As the use of IoT devices continues to grow, implementing end-to-end encryption will become increasingly important for ensuring the security and privacy of sensitive IoT data.
2.5 Industry and Government Collaboration
In late 2021, the UK and Singapore governments became the first to announce obligatory security requirements for specific categories of IoT devices. Due to IoT data security risks, other countries have also defined guidelines, best practices, certifications, or labeling efforts for IoT devices. However, adoption among IoT device makers and vendors has been slow.
The National Institute of Standards and Technology (NIST) has been working on establishing cybersecurity guidelines for IoT devices. In June 2022, NIST incorporated consumer IoT cybersecurity criteria into its family of IoT cybersecurity guidance. NIST is also working with the IoT industry to design, standardize, and test solutions for IoT security controls.
By discussing IoT device security concepts and establishing guidelines in collaboration, the industry and the government can foster adoption of general methods to protect IoT devices from cybersecurity breaches. Such cooperation can be crucial in ensuring that IoT devices are secure from cyber threats and that IoT device makers and vendors adopt best practices for IoT device security.
3 Conclusion
The trends in IoT data security showcase several proactive measures that can be taken to protect sensitive data in a rapidly evolving technological landscape. In addition, organizations are moving towards a more comprehensive approach to IoT data security with the emergence of AI-powered security solutions, blockchain technology, and the shift to zero-trust security frameworks.
As IoT devices continue to proliferate, organizations must prioritize security and data protection to prevent data breaches and cyberattacks. This emphasizes the need for collaboration between industry and government to strengthen security measures and improve IoT device security by building with a ‘secure by design’ approach.
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Enterprise Iot, Infrastructure
Article | May 31, 2023
Discover the crucial role of big data capabilities in unlocking the potential of IoT for businesses. This article covers their synergy, challenges, and value in decision-making and revenue generation.
Contents
1 Why Big Data and IoT Matter for Businesses
2 Understanding Synergy of Big Data and IoT
2.1 How IoT generates Big Data
2.2 Challenges of Processing Big Data from IoT Devices
2.3 Importance of Big Data in IoT Applications
3 The Value of Big Data and IoT for Businesses
3.1 Improved Decision-making for Businesses
3.2 Generate New Revenue Streams
4 Final Thoughts
1. Why Big Data and IoT Matter for Businesses
The internet of things (IoT) is connecting all types of physical assets to the internet, from smart wearables that track wearer’s vitals to connected industrial units that can report any malfunctions automatically. Big data in IoT is a natural outcome with the growth of IoT devices, with an immense surge in the amount of data being generated.
There are currently over 13 billion connected IoT devices worldwide.
(Source – Techjury)
This data is extremely valuable to businesses as it can help streamline operations, predict trends, and diagnose device issues. Certain functions of IoT devices that are crucial for modern businesses, such as enabling predictive maintenance, depend on the analysis of the data generated every second. However, to maximize the ROI from their IoT ecosystem, businesses must first manage and process the vast amounts of unstructured data they produce. This is where big data capabilities come in.
2. Understanding Synergy of Big Data and IoT
Big data and the IoT are fundamentally different concepts, but are closely connected. Big data is a term that is used for a great amount of data that is characterized by volume, velocity, variety and veracity (or the ‘trustworthiness’ of data). The IoT is a term for physical devices or objects linked to the internet using an assortment of technologies. Understanding the synergy between these two technologies will be critical for businesses looking to leverage their full potential.
2.1 How IoT generates Big Data
IoT is one of the primary drivers of big data growth. The vast number of interconnected devices in the IoT ecosystem generates a massive amount of data every second. This data includes information on user behavior, device performance, and environmental conditions, among others.
The nature of this data makes it challenging to store, process, and analyze using traditional data management tools. This is where big data technologies such as Hadoop, Spark, and NoSQL databases come in, providing the ability to manage massive amounts of data in near-real-time, enabling critical applications of big data in IoT. For businesses, processing IoT data is synonymous with processing big data, due to the nature of the data generated by an IoT ecosystem.
2.2 Challenges of Processing Big Data from IoT Devices
IoT data processing is a complex and challenging task due to several reasons. Firstly, the sheer volume of data generated by these devices is enormous and is only increasing. This requires a robust infrastructure and specialized tools to store, manage, and analyze the data efficiently.
This data is also generally unstructured, heterogeneous, and complex, making it difficult to process using traditional data management and analysis techniques. Moreover, it is often noisy and may contain errors or outliers, which can impact the accuracy of data analysis. Businesses also face a challenge when securing such vast amounts of data. Since IoT devices collect sensitive information such as personal and financial data at scale, it is critical to ensure that data is encrypted, transmitted securely, and stored safely.
Additionally, IoT devices often operate in remote locations with limited connectivity, making it challenging to transmit data to the cloud for storage and analysis. As IoT devices continue to proliferate and generate increasingly large amounts of data, businesses must adopt big data technologies to gain actionable insights from this data.
2.3 Importance of Big Data in IoT Applications
There are several use cases of the IoT where processing large amounts of data is essential. It plays a critical role in IoT applications, providing businesses with valuable insights that can be used to optimize processes, reduce costs, and improve overall efficiency. By collecting and analyzing large amounts of data from IoT devices, businesses can gain a better understanding of customer behavior, machine performance, and other critical metrics.
For example, big data in IoT can be used to identify patterns in customer behavior, allowing businesses to tailor their marketing efforts and improve customer engagement. Additionally, IoT devices can be used to collect data on machine performance, allowing businesses to identify potential problems before they occur, minimize downtime, and optimize maintenance schedules. The value of big data in IoT applications lies in its ability to provide businesses with real-time insights that can be used to drive growth, reduce costs, and improve overall efficiency.
3. The Value of Big Data and IoT for Businesses
Businesses looking to integrate big data in IoT must first consider their data storage and analytics capabilities. By understanding the value of big data technology in capturing and analyzing IoT-generated data, businesses can unlock insights that can help them make better decisions, optimize processes, and create new business opportunities.
3.1 Improved Decision-making for Businesses
IoT and big data technologies offer businesses a wealth of data that can be used to make better-informed decisions. By integrating IoT sensors and devices with their operations, businesses can collect real-time data on customer behavior, operational performance, and market trends. This data can then be analyzed using big data analytics tools to generate valuable insights that can inform decision-making.
For example, operational data can be analyzed to identify inefficiencies and areas for optimization, helping businesses reduce costs and improve efficiency. With the right data storage and analytics capabilities, businesses can leverage the power of IoT and big data to gain a competitive advantage and make better-informed decisions that drive growth and success.
3.2 Generate New Revenue Streams
By leveraging the vast amount of data generated by IoT devices and analyzing it with big data analytics tools, businesses can gain insights into customer behavior, market trends, and operational performance. These insights can be used to create new revenue streams and business models, such as subscription-based services, pay-per-use models, and predictive maintenance services.
For example, IoT sensors can be used to collect data on equipment performance, allowing businesses to offer predictive maintenance services that help prevent equipment breakdowns and reduce downtime. Similarly, customer data can be analyzed to identify new revenue opportunities, such as personalized product recommendations and targeted advertising. With the right strategy and investment in IoT and big data technologies, businesses can unlock new revenue streams and create innovative business models that drive growth and success.
4. Final Thoughts
Big data in IoT is becoming increasingly important for businesses, and the future prospects are bright. As IoT continues to grow and generate more data, businesses that can effectively analyze it will gain a competitive advantage, leading to increased efficiency, reduced costs, and higher ROI. To fully realize the benefits of IoT, businesses must develop big data analytics and IoT devices in tandem, creating a feedback loop that drives continuous improvement and growth. By embracing these technologies, businesses can make data-driven decisions and unlock new insights that will help them thrive in the years ahead.
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