Sustainable farming - a spatio-temporal adaptation of late blight disease prediction using multi-modal data

Indiscriminate use of chemicals for farming leads to various environmental pollution- air, land, and water. Judicious use of chemicals in farming has a huge environmental benefits as well as reduction in farming cost. In this paper, we proposed a novel spatio-temporal adaptation techniques to localize the pest/disease risk using multi modal data - geo-spatial location, weather, satellite observations, and plant imageries. To illustrate the efficacy of the method, we demonstrated a case study with potato farmers which fulfilled the dual objectives of positively bringing food security and safety to our society while enabling sustainable and profitable operations.