Data Processing & Analysis

We are working on data compression algorithms with energy as a constraint. Our compression algorithms are adaptive to energy availability. Data analysis calls for using crop simulation tools such as APSIM to predict the crop yield.

The Sensor data collected at the aggregating node is given as input to the data compression algorithm which is based on the energy availability. The compressed data is bundled and sent to the datamule which collects these bundles using Delay/Disruption Tolerant Networking over Bluetooth or Wi-Fi.

Data Compression

Fig. Energy Efficient data compression algorithm


The compressed data received at the Server will decompress the data and reconstructs the original data. The original data is now fed to crop simulation tools like APSIM. APSIM is internationally recognized as a highly advanced simulator of agricultural systems. It contains a suite of modules which enable the simulation of systems that cover a range of plant, animal, soil, climate and management interactions.

esw vs Rain

Fig. Simulation result for esw and rain against date. CourtesyAPSIM


The graph shown was generated using APSIM. In this context, we have selected the crop to be wheat and soil type as Grey Vertosol-Cecilvale. Water was assumed to be filled 10% from top. Here we can notice that whenever there is a peak in rain value esw will also give a peak.