PESTO-BOT

Agriculture is the backbone of our country. Digital technologies are being used to improve and increase the production of the crops. This proposes to use of Robot in the agricultural sector. The robot can be controlled autonomously. Farmers are reaching out to agricultural robot to help mitigate the problems of pest control and increase the yield of crops. The aim of this project is to create an autonomous spraying robot that will decrease pest and minimize the usage of pesticides and decreases human health Impact, allowing farmers to be protected and labour intensity can be reduced. The bot will be trained for route planning, navigation systems, spraying mechanism and obstacle avoidance with multi-sensor module integration. First the robot detects the pest using thermal camera and the algorithm of Image processing is applied in which the images of the leaves affected by pests is captured by using a digital camera. The leaves with pest images are processed for getting a grey-coloured image and then using feature extraction, image of the pest is detected. Once the pest is confirmed the nozzle gets activated and it sprays pesticides only to the particular area where the pest is present. The CAD model of the Bot is designed using FUSION 360. Belt drive mechanism is designed for the movement of the Bot. There is a robotic arm which consists of a sprayer and a tank is present to store the pesticides and there is a light pole which tell us the location of the bot.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-27
DOI
https://doi.org/10.5281/zenodo.14916995
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PESTO-BOT

Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

PESTO-BOT

article en

Abstract

Agriculture is the backbone of our country. Digital technologies are being used to improve and increase the production of the crops. This proposes to use of Robot in the agricultural sector. The robot can be controlled autonomously. Farmers are reaching out to agricultural robot to help mitigate the problems of pest control and increase the yield of crops. The aim of this project is to create an autonomous spraying robot that will decrease pest and minimize the usage of pesticides and decreases human health Impact, allowing farmers to be protected and labour intensity can be reduced. The bot will be trained for route planning, navigation systems, spraying mechanism and obstacle avoidance with multi-sensor module integration. First the robot detects the pest using thermal camera and the algorithm of Image processing is applied in which the images of the leaves affected by pests is captured by using a digital camera. The leaves with pest images are processed for getting a grey-coloured image and then using feature extraction, image of the pest is detected. Once the pest is confirmed the nozzle gets activated and it sprays pesticides only to the particular area where the pest is present. The CAD model of the Bot is designed using FUSION 360. Belt drive mechanism is designed for the movement of the Bot. There is a robotic arm which consists of a sprayer and a tank is present to store the pesticides and there is a light pole which tell us the location of the bot.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 43%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.