Energy-Efficient VLSI Design for Remote Sensing Applications

Abstract

Remote sensing systems require robust and energy-efficient processing capabilities, particularly in satellite-based or autonomous deployments where power is a scarce resource. Very Large Scale Integration (VLSI) design plays a crucial role in enabling real-time data acquisition, compression, and interpretation under strict energy and space constraints. This paper explores architectural and circuit-level strategies for developing low-power VLSI systems in remote sensing platforms. Key techniques include clock gating, dynamic voltage scaling, and energy-aware data path optimization. We also evaluate the trade-offs between performance and energy consumption using case studies involving image processing for earth observation. A comparative analysis of different VLSI power reduction methods is presented, along with a discussion on future trends such as neuromorphic computing and AI accelerators for embedded remote sensing.