International Journal Of Engineering Technology And Management Sciences

AUTHOR(S)

Bhoomika K.M., Bhuvan J., Hruday B.N., Mithun V.P., Dr. Pavithra G., Dr. Sindhu Shree M., Dr. T.C.Manjunath, Aditya T.G., Sandeep K.V., Rajashekar M. Koyyeda, Dr. Suhasini V.K., Dr. Vijayakumar K.N.

DOI: https://doi.org/10.46647/ijetms.2023.v07i01.048

ABSTRACT
This paper gives the design and development of a precision farming robot. Since a long time ago, agriculture has been a significant part of the Indian economy. 18% of India's gross domestic product is produced by the agriculture sector (GDP). A better answer for precision agriculture is provided by robotics and the internet of things. Selective harvesting is necessary when picking fruits or vegetables like tomatoes and apples. In traditional farming, each fruit is hand-picked by a worker, requiring a huge amount of labour to carry out selective farming. We suggest a robot that helps farmers with a variety of labor-intensive chores, such as selective crop harvesting and qualitative segregation, while also simultaneously providing data on crop health, soil nutritional status, and crop shelf-life detection. An android application is used to analyse, process, and send the obtained data to the farmer. Later, the weight, colour, and health of the particular crop are checked to grade its quality. The fruit is subsequently moved into the designated container after being graded. Spoiled or overripe fruits and vegetables would be plucked and dropped so as not to interfere with the plant's growth. A harvesting arm on the proposed robot would reach the fruit or vegetable and pick it from the plant or tree. The fruit would then be transferred to the appropriate container. With the aid of the app, the user would be able to give the device a certain task based on his requirements. Crop health monitoring, segregation, and selective harvesting all require image processing using a camera. Additionally, using image processing, illnesses are found. The image segmentation and pre-processing are being done by us. The guided, supervised, and advanced machine learning technique k-nearest neighbours (KNN) is used to build solutions for both classification and regression issues. This gives the farmer useful information that is essential for choosing the correct insecticides, herbicides, and fertilisers for higher yield. Every nation's primary issue and developing topic is agriculture automation. The need for food is rising rapidly as the world's population is growing at an extremely rapid rate. Farmers must apply toxic pesticides more frequently since their traditional methods are insufficient to meet the growing demand. This damages the soil. This has a significant impact on agricultural practises, and as a result, the land remains unproductive and desolate. You can employ a variety of automation techniques, including IOT, wireless communications, machine learning, artificial intelligence, and deep learning. The work given here is a mini-project that is taken up as a part of the curriculum completed by lectronics and communication engineering students in the second year of the electronics & communication engineering department at Dayananda Sagar College of Engineering in Bangalore.

Page No: 320 - 324

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How to Cite This Article:
Bhoomika K.M., Bhuvan J., Hruday B.N., Mithun V.P., Dr. Pavithra G., Dr. Sindhu Shree M., Dr. T.C.Manjunath, Aditya T.G., Sandeep K.V., Rajashekar M. Koyyeda, Dr. Suhasini V.K., Dr. Vijayakumar K.N. . A novel design for carrying out automated agricultural tasks using an agriculturally developed robot . ijetms;7(1):320-324. DOI: 10.46647/ijetms.2023.v07i01.048