Fog-enabled WSN system for animal behavior analysis in precision dairy
This paper proposes wireless sensor networks as a parallel and distributed computing platform for neurocomputing. The proposal entails leveraging the existing wireless sensor networks technology to serve as a hardware-software platform to implement and realize artificial neural network algorithms in fully parallel and distributed computation mode. The study describes the proposed parallel and distributed neurocomputing architecture, which is named as WSN-ANN, and its use as a hardware platform on a case study. A Hopfield neural network, which is configured to solve the minimum weakly connected dominating set problem, is embedded into a wireless sensor network. Simulation study results indicate that the proposed computing platform based on wireless sensor networks, WSN-ANN, is feasible and promising to serve as a parallel and distributed neurocomputer.