Optimal Placement of Radio Frequency Energy Harvester for IoT-Based Applications

The Internet of Things (IoT) is redefining how we interact with our surroundings, from smart home gadgets to crucial industrial applications. The increasing deployment of IoT devices has necessitated efficient and sustainable energy solutions. Harvesting energy from radio frequency (RF) signals has developed as a sustainable way to power IoT devices by converting ambient RF signals into usable electrical energy as we are surrounded by powerful electromagnetic waves in the 5G communication era. Capturing maximum power in RF energy harvesting is a primary challenge due to the low power density of radio frequency energy. Positioning the RF harvester in the ideal location is very important for maximizing the capture of ambient RF waves. A Particle Swarm Optimization (PSO) based method is deployed for the optimal positioning of RF energy harvesters in IoT environment to maximize energy capture and device performance. The PSO algorithm is employed to find near-optimal solutions by simulating particle movements in a multidimensional search space. This optimization considers factors such as RF signal intensity, frequency and the spatial distribution of RF signal sources to determine the optimal locations for deploying energy harvesters. The placement strategy dynamically adjusts to maximize energy harvesting by moving towards the RF source with highest available power while maintaining a balance between coverage and energy harvesting. Results indicate that optimal harvester placement significantly enhances energy efficiency and extends the operational lifespan of IoT networks, thereby contributing to more sustainable and autonomous IoT deployments.