Authors : Kota Sadhana; Kotaparthi Charanya; Kundarapu Varshith; Shaik Abbas Ahmed

Volume/Issue : Volume 9 - 2024, Issue 4 - April

Google Scholar : https://tinyurl.com/2y47vcud

Scribd : https://tinyurl.com/2h39kta9

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR2108

Abstract : Climate change has an impact on crops, fruits, vegetables, and pest infestation, hence agricultural output is a top priority for most nations. As a result, professional growers have the problem of reaching maximum output results, and greenhouses have emerged as an excellent choice for ensuring these results. Farmers can employ innovative technologies inside greenhouses to prevent insect damage to plants and increase indoor growth through climate management. However, in order to manage agricultural fields and greenhouses successfully, farmers must now use Industry 4.0 technology such as robotics, Internet of Things devices, machine learning software, and so on. In this setting, sensor deployment is critical for gathering data and obtaining knowledge to help farmers make decisions. As a practical option for small farms, this research proposes an autonomous robot that drives along greenhouse crop paths with previously specified routes and can collect environmental data provided by a wireless sensor network when the farmer has no prior knowledge of the crop. An unsupervised learning method is used to cluster the optimal, standard, and deficient sectors of a greenhouse in order to identify improper crop development patterns. Finally, a user interface is built to assist farmers in planning the robot's route and distance while gathering sensor data to monitor crop conditions.

Keywords : Smart Farming; Robotics; Greenhouse; Environmental Monitoring; Auto Mation Optimization; Wi-Fi Camera; Sustainability.

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