Vol. 12, Special Issue 12 (2023)

Author(s):
RG Jakasania, Ajay Makwana and R Yadav

Abstract:
Weeding is an essential practice in crop cultivation as it removes unwanted plants that compete with cultivated crops for resources. In India, small-scale farmers rely heavily on manual labor for weeding due to the high costs of herbicides and weed management equipment. To address these challenges, the agricultural sector is adopting mechanization and herbicide usage. However, small landholding sizes and cost factors hinder the adoption of these technologies. Intra-row weeding, which involves removing weeds within crop rows, is currently done manually and requires improvement to make it more efficient and less labor-intensive. Automated or semi-automated weeding technologies can reduce time and effort. Advancements in machine learning and computer vision can accurately identify and target weeds, minimizing damage to crops. The development of an automated inter and intra-row weeder aims to minimize plant damage and increase productivity. The weeder utilizes a frame, tines, inter and intra-row blades, ultrasonic sensor, D.C. motor with drivers, microcontroller, battery, wooden box, and sensor and motor holders. Ultrasonic sensors differentiate between crops and weeds based on their height, allowing precise weed removal without damaging crops. The weeder significantly reduces manual labor, covers large areas quickly, and integrates easily with existing farm machinery. It offers a cost-effective, efficient, and precise solution for weed control in agriculture, improving crop yields and reducing labor costs.