SDGs are internationally accepted development targets that are used to enhance social-economic and environmental welfare. Nonetheless, a solution to the SDG problems that would be based on technology is quite difficult to implement in areas with low connectivity and remote locations because of the poor infrastructure. The interesting alternative that might allow to push back the continuous connectivity with the cloud is edge computing, i.e., processing data locally. The present paper discusses how edge computing may enable applications aimed to achieve SDGs, specifically, health monitoring, precision agriculture, water quality monitoring, and education, especially in underserved settings. An architecture combining the edge topologies, real-time sensor and decentralized intelligence is demonstrated and tested within the simulation that witnesses low-bandwidth network conditions. Findings established that edge-based systems play a paramount role in improving data responsiveness levels, lowering the delays in the transmission process and facilitating local decision-making. This analysis finds that edge computing is a sustainable process of enabling technology security and coverage in remote societies.
D. Srikanth (Sat,) studied this question.