Improving Edge Computing Efficiency and Scalability through Very Large Scale Integration of Sensors for Smart Internet of Things Systems

There is a rising need for effective edge computing solutions due to the rising need for low-latency applications and real-time data processing in Internet of Things (IoT) systems. When it comes to the demanding needs of IoT applications, traditional cloud computing methods frequently fall short. This is because of problems with scalability, bandwidth limits, and latency. The goal of this research is to make edge computing systems more efficient and scalable by using Very Large Scale Integration (VLSI) of sensors. These sensors can give high-throughput data collecting and processing capabilities at the edge of networks. In order to improve the performance and functionality of edge computing devices, the study investigates the possibility of integrating sophisticated VLSI techniques with IoT systems. We want to improve the edge processing power, cut down on data transmission overhead, and make real-time decisions as quick as possible by integrating VLSI-based sensors into the system design. The goal of this research is to make the system more scalable so that it can manage a high number of Internet of Things devices without sacrificing performance by improving the design and placement of sensors. We provide a modular architecture for scalable edge computing that incorporates numerous very large scale integration (VLSI) sensors that can efficiently process sensor data locally. This system is perfect for smart cities, industrial automation, healthcare, and environmental monitoring systems because of its modular design, which makes it easy to expand to accommodate the increasing number of Internet of Things devices. Building a prototype with cutting-edge VLSI sensor technology and doing rigorous tests to measure its processing power, scalability, and energy efficiency will allow us to assess the suggested system’s efficacy. We anticipate that the outcomes will demonstrate notable enhancements in data throughput, processing efficiency, and system scalability, leading to the eventual realization of smart IoT systems that are more efficient, responsive, and energy conscious. Developing next-generation Internet of Things (IoT) systems that can support sophisticated, large-scale applications with less reliance on centralized cloud resources is the goal of this research. This will be achieved by improving the efficiency and scalability of edge computing through the integration of VLSI-based sensors.