Industrial IoT, IoT Security
Article | July 11, 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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Enterprise Iot
Article | July 20, 2023
Artificial intelligence is becoming increasingly crucial in IoT applications and deployments. Over the past two years, investments and acquisitions in firms that combine AI and IoT have increased. IoT platform software from top suppliers now includes integrated AI features, including machine learning-based analytics.
When artificial intelligence is linked with the internet of things, we get Artificial Intelligence of Things (AIoT). The prime motive for combining AI and IoT is that, while IoT devices are used to gather data and send it to a cloud or other location where it can be stored using the internet, AI, which is regarded as the brain of AIoT, is what actually aids in decision-making and simulates how machines would act or react.
Other artificial intelligence (AI) tools, such as speech recognition and computer vision, can assist reveal patterns in data that previously needed human evaluation.
AI applications for IoT-enabled companies help them avoid several issues:
Preventing expensive unplanned downtime
Predictive maintenance can lessen the adverse economic effects of unplanned downtime by employing analytics to anticipate equipment failure and arrange orderly maintenance processes. In order to predict equipment failure, machine learning enables the discovery of patterns in the continuous streams of data produced by today's technology.
Operational efficiency advancement
IoT with AI capabilities can also increase operational effectiveness. By processing continuous data streams to find patterns invisible to the human eye and not visible on simple gauges, machine learning can predict operating conditions and identify parameters that need to be adjusted immediately to maintain ideal results, just as it can predict equipment failure.
Improved risk management
IoT and AI-powered applications enable businesses to automate for quick reaction, better analyze and predict a range of hazards, and control worker safety, financial loss, and cyber threats.
Finding an IoT system that does not incorporate AI could soon be uncommon. With the help of AI, organizations can truly enhance the potential IoT and effectively put it into use for improving the overall functioning.
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Industrial IoT, IoT Security
Article | July 12, 2023
The Internet of Things (IoT) and Industrial Internet of Things (IIoT) markets have experienced explosive growth as a result of the digital industrial revolution that followed the COVID-19 epidemic. To fully benefit, however, organizations have had to handle security concerns associated with these revolutionary technologies. Therefore, finding the correct security strategy is crucial for any organization because of the increasing dependency on IoT and IIoT to manage essential business systems.
IoT and IIoT can be implemented quickly, but they come with inherent vulnerabilities. This risks businesses from cyberthreats such as device theft, spoofing, denial of service attacks, and data breaches or siphoning. Attacks of this nature adversely affect an organization's operations, finances, safety, and reputation.
Many IoT and IIoT devices have passwords hard-coded into their firmware, making it challenging to patch or update security, which is a significant problem. Even when security is deployed on a device, it can usually be bypassed by taking advantage of a variety of known weaknesses. As a result, IT teams may find it challenging to identify an occurrence when IoT or IIoT devices are compromised before affecting systems and data.
Mitigating IoT and IIoT Security Risks
Separate IIoT and wireless devices from the SCADA or ICS network. Micro-segmentation allows only authorized device connectivity in certain circumstances.
Control network access by monitoring what connects and validating each device's security.
Demand visibility across all enterprise security networks and devices. This should be centralized so all devices, networks, risks, traffic, and policies can be handled in real-time across production and IT environments.
Use an intrusion protection system (IPS) to identify threats and patch IoT and IIoT devices virtually. Counter unexpected attacks with active protection and deception techniques.
It's crucial to check that security solutions can grow automatically to meet business requirements before using them. This entails responding to network changes, foreseeing risks and controlling them proactively, and offering real-time threat intelligence.
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Enterprise Iot
Article | August 3, 2022
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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