Issue link: https://resources.mouser.com/i/1499313
Renesas 2023 19 bandwidth and power to support large and potentially lengthy data transmissions. Potential latency issues are also a factor; as the time expended during transmission increases, so does the need for higher server capacities to handle all incoming data. Situations may also arise where IoT devices lack a stable internet connection, and decisions must be made at the endpoint. Solutions that can support the consumer experience using analytics at the endpoint are often required. Analytics of Things (AoT) is a term used to describe the analysis of data generated by IoT devices. AoT makes it possible to operate business intelligence within an application rather than a data warehouse. It also assists in understanding patterns, detecting anomalies, predicting potential issues, setting maintenance intervals, and optimizing processes. Over the years, organizations have relied on data analytics based on a centralized architecture for their data-driven planning and visions of the future. The data is increasing every second, and there is a requirement for a revolutionary approach to overcoming data transfer latency, improving privacy, and meeting customer expectations. The real- time response has especially become necessary after the convergence of AI, 5G, and IoT. Distributing intelligence across the end of the network provides an opportunity for more efficient data analytics and real-time decision-making at the endpoints with little to no latency. Performing these functions directly on endpoint devices with low- processing capabilities is referred to as endpoint data analytics (Figure 3). The Data Science Support System Various technologies and sensors facilitate the processing of data analytics at the endpoint. Sensors are required not only to gather and accumulate data but also to assist in assessing and understanding the surrounding environment. Commonly implemented types of sensors include GPS for determining location and thermometers and barometers for measuring temperature and pressure. Cameras, lasers, and radar/ sonar can also be used to detect people and/or objects nearby. Communication technologies such as Wi-Fi and 5G assist in gathering and transmitting data. The data is then fed into data science algorithms that play the central role in assessing the data and recommending potential courses of action. In certain use cases, the outcome of the analytics performed at the Figure 3: Endpoint data analytics. (Source: Renesas Electronics)