Why Should You Set up Smarter IoT Devices at the Edge?
Why should you set up smarter IoT devices on the sidelines?
Smart devices get smarter, learn our habits and free us from routine tasks. Smart machines and the integration of futuristic technologies have made daily life easier. According to analyst projections, IoT growth projections for 2025 range from nearly 25 billion connected devices by GSMA to 43 billion by 2023 by IDC and about 56 billion by Mckinsey.
It finds that even at the lower end of projections, the number of IoT devices is expected to more than double over the next few years. Additionally, as the market matures, IoT solutions will definitely become more data hungry due to the rise in video applications and the increased processing requirements of sophisticated AI and analytics technologies.
To ensure that data processing speeds can keep up with the pace of IoT growth, solution providers would need to innovate quickly across the IoT data chain.
Edge computing is a must
Edge computing is the first step in the IoT data chain where data can be processed before being sent to application servers for further analysis. Earlier generations of IoT solutions collected data and sent it to the server in unprocessed raw form. While this approach is still suitable for applications such. B. Take a volume measurement on a fuel tank once a day and notify the end user when the levels get low. However, it simply cannot support applications that require higher bandwidth or lower latency.
Imagine a video telematics solution for fleet operators that records external footage in the event of an accident while simultaneously monitoring the driver's vigilance. Without edge computing, this solution presents two problems: without the intelligence to detect an accident, the device must transmit a large amount of (ultimately unimportant) data at high cost and without the ability to detect an accident Issue a warning to correct the behavior. In addition, such solutions can encounter situations where data needs to be processed immediately. However, the cellular signal was disturbed. This solution requires a way to minimize unnecessary data transmission, reduce latency, and process data locally in the event a signal fails to provide its value.
Activate security at the periphery
As IoT solutions become more prevalent in our daily lives, the network of devices becomes available to hackers for malicious purposes. The scale of these attacks has increased significantly in recent years. For example, the main Distributed Denial of Service (DDoS) attack in 2016 brought down sites like Twitter, Netflix, CNN and many others. This was achieved by taking control of many connected video cameras, DVRs, and other devices and using them to flood the most extensive Domain Name System (DNS) server with traffic until it crashed.
"Our personal information and security will be much more vulnerable to cyberattacks if we don't have proper security control systems. Cardiac devices that monitor and control patient heart function could be hacked and controlled by malicious actors; hackers could monitor baby sleep in order to gain access Spy on your child and your car could be taken over and held remotely, "said Ranjeet Koul, APAC & MEA vice president and country manager, Aeris Communications.
All of these examples underscore the critical importance of edge security. Cloud servers have robust security measures. Data needs to be backed up as early as possible in the IoT data chain to ensure that the solution is protected from security breaches. Password management, support for wireless firmware updates, and encryption in local Wi-Fi networks and cellular gateways are important components of an IoT security protocol.
Don't create a "data museum"
As the number of connected devices doubles in the next few years and these devices send more data, there is a risk that a "data museum" or a place where data is stored will collect dust and lose its value. Only analyzed information is helpful. For example, suppose the back-end servers are overloaded with data from tens of billions of devices. In this case, it can become prohibitively expensive to send, process, and search this data, effectively rendering it unusable. More innovative processing on the fringes regulates the amount and quality of data transmitted to cloud servers and ensures that the amount of data in the cloud does not exceed our ability to process and analyze.
Conclusion
In the future, more devices with intelligent edge functions are expected to be used in the Internet of Things. Neuromorphic or in-memory computing, spiking neural networks and even quantum AI could be part of the AI-accelerated future. This also makes it easier to implement algorithm training for machine learning on the edge. In short, IoT with a smart edge will pave the way for a new human-AI interface. As technology becomes more sustainable, it will be an exciting time for designers, engineers, businesses, and consumers.
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