“A Task Offloading and Edge Computing Framework for Enhanced Energy Efficiency and Reduced Latency in IoT Image Recognition Applications”

The rapid growth of the Internet of Things (IoT) has revolutionized many areas, but it also presents new challenges, particularly in energy efficiency. IoT devices are often small, with limited battery life, making energy-saving solutions crucial. Edge computing, along with task offloading, has become a key strategy to improve energy efficiency while maintaining good performance. This paper explores some offloading methods, like edge computing (EC), and cloud computing, to reduce energy use while addressing latency and network traffic issues. We present a mathematical model that evaluates the balance between energy, speed, and bandwidth, supported by extensive simulations. The results show that edge computing offloading can significantly reduce energy consumption and lower latency in the IoT ecosystems.