Low Cost IoT and ML based Pesticide Level Detection in Fruits and Vegetables

The escalating usage of pesticides, steroids, and fertilizers pose severe health risks to consumers. Particularly concerning is the infiltration of harmful pesticides into fruits and vegetables further exacerbates existing health conditions, rendering them incurable. Addressing this issue requires a low-cost comprehensive solution to analyze pesticide levels in commonly consumed farm produces. This paper proposes a novel approach utilizing hardware-software co-design integrated with sensors such as temperature, pH, gas, and humidity, etc interfaced with Arduino microcontroller to detect pesticide presence in real-time accurately. The threshold for safe pesticide levels for various farm fresh products is adaptively set by Random Forest Algorithm that aids in identification of pesticides. To leverage IoT technology, data is transmitted to the ThingSpeak server, facilitating easy monitor of agricultural produce quality and safety. So that agricultural products starting from production to sales is streamlined, ensuring high-quality and safe food for consumers. Thus, risk management and traceability throughout the supply chain in real-world testing validates the efficacy of the pesticide detection device, promising a significant step towards safer food consumption.