Design and analysis of wireless sensor network framework for greenhouse monitoring

Abstract

The thesis presents an end-to-end survey; starting from the layout of sensors in greenhouses, sampling techniques to choose transmission interval of sensed data, routing algorithm for selection of a path for data transmission, communication technologies, prediction models, and decision-supporting techniques adopted in greenhouses for efficient integration of WSN. It is important to address crucial challenges of energy conservation for the sustainability of WSN-equipped modern greenhouses. In a WSN setup, most of the energy is consumed by a transceiver. So sampling technique is designed to choose appropriate samples to be transmitted, out of raw sensed data. This research work proposes a Variance Adaptive Sporadic (VAS) sampling technique that particularly capitalizes on slow dynamics of the greenhouse. VAS sampling is tested for a tomato greenhouse dataset and re-validated for another two greenhouse datasets. The proposed system saves on energy consumption without compromising the reliability of data. Further in a greenhouse, routing of sampled data to a base station is challenging due to vegetation interference and growing phases of the crop. This research work proposes a hybrid Path Loss based Distance Vectored (PLDV) routing protocol. PLDV protocol is simulated with propagation loss and total path loss. Further, the effect of maturity of the crop is also considered. PLDV protocol is tried over three cases of 10%, 20%, and 50% routing links lost due to hindrance by growing crops. PLDV protocol is able to sustain communication even after 50% of links among nodes are lost. Thus the designed WSN framework caters to the application-specific requirements of greenhouse monitoring. newline