Analysis of post harvest losses: An Internet of Things and machine learning approach
Reduction of post harvest losses is a critical component of food security. World population is increasing at an alarming rate and thus is the food requirement. Due to limited cultivable land, increasing the food production to meet the needs of people, solely, cannot be the solution. In this paper, we have proposed to build an end to end system for farmers and warehouse managers to reduce post harvest losses. It will consist of a notification suggestion system which will include data about the current status of farm, suggestions about correct harvesting time and diseases that might affect the crop in its cultivation stages. The system will also include a prediction system for warehouse managers which will suggest the correct dispatch sequence of the stocks and also the optimum temperature and humidity at which one or more crops can be transported so as incur minimum storage and transportation loss. Here, for the prediction analysis and suggestions, various statistical and probabilistic techniques such as classification and regression are used.
2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT)