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data source. By processing data locally on the device itself or at nearby edge servers, you can significantly reduce the amount of data transmitted over networks, minimizing energy consumption and latency while enhancing security and resilience. To appreciate the potential of edge processing, you must first understand the energy cost of data transmission. Landauer's principle states that moving or processing one bit of data requires a minimum energy of kT natural log of two. Transmitting one gigabyte of data can consume between five to seven watt-hours, depending on the type of network, distance, and efficiency. When you consider the millions of IoT devices generating data around the clock, the cumulative energy cost of transmitting all that data to the cloud becomes staggering. Edge Analytics and AI for Power Optimization Edge processing alleviates the energy burden by strategically processing data at its source. Implementing edge analytics to detect anomalies locally through the use of thresholds or spectral features can reduce power consumption by up to 80%. This is particularly important for IoT devices deployed in remote locations or with limited power resources, where C h a p t e r 3 | E d g e P r o c e s s i n g a n d A n a l y t i c s every bit of saved energy can significantly extend the device's lifespan and lower maintenance costs. Edge processing becomes even more compelling when combined with artificial intelligence. Leveraging edge AI optimizes computational efficiency while maintaining high accuracy, enabling IoT devices to make smart decisions in real-time without relying on cloud servers. This approach reduces energy consumption, minimizes latency, and enhances security by decreasing the attack surface and the risk of data interception during transmission. The benefits of edge AI extend beyond energy efficiency. By processing data locally, edge AI enables faster response times, making it ideal for applications that require real-time decision-making. Furthermore, edge AI allows for greater privacy and data sovereignty, as sensitive data can be processed and acted upon without leaving the device. 10 Engineering Reliable Industrial Automation With Sensor Fusion