Plant Health Condition Recognition Using Neural Network Smart Agriculture System
- DOI
- 10.2991/978-94-6463-662-8_34How to use a DOI?
- Keywords
- Precision Agriculture; Neural Networks; Digital Image Processing; Green House Monitoring; Max Pooling 2D
- Abstract
Agriculture is the backbone of our country’s economy. At present cultivation has turned into more significant to meet the needs of the human race. Though, agriculture necessitates irrigation and by each year we have additional water utilization than rainwater that became serious for growers to discover ways to preserve the water while attaining the highest acquiesce. Usually, the present irrigation methods were physically controlled. To use irrigation effectively and efficiently, semi-automated and automated approaches are recommended in place of these methods. Automated sensor-based irrigation relies on a soil moisture sensor to monitor soil moisture levels and send a signal to a Raspberry Pi controller, which then irrigates crop fields.
The paper is to develop a smart irrigation monitoring scheme with Raspberry Pi. The parameters concerned are mainly soil moisture and temperature. This scheme is a substitute for traditional farming schemes. It helps the cultivator to know crop status at home or sitting in any part of the globe. This reduces energy consumption, the efficiency and saves time. The work aims to manage motors without human intervention and also to watch live streaming of the field on his Android mobile phone using Wi-Fi. It offers instantaneous data on the field. Now water is supplied depending on the actual needs of the crop field. So, it lessens water logging and shortage. When a pre-defined range of temperature and moisture sensors varies, the Raspberry Pi turns the pump ON. This scheme may execute on a large scale for farming functions.
The images of plants are obtained with a web camera and practiced in digital image processing. The waterlessness of the leaf and infection affected the leaf were found and information will be sent to H/W. The key advantage scheme is the implementation of precision agriculture (PA), which maximizes agricultural output while also maximizing fertilizer & water use efficiency and also aids in field weather investigation. The hardware can also receive different data from sensors. The collected data are sent to the cloud through Wi-Fi for database management and analyze the data and provide feedback through the Telegram app or think speak.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Y. V. Siva Reddy AU - N. Dinesh Kumar AU - B. V. Rami Reddy AU - Harinatha Reddy Chennam AU - Ravi Sankara Reddy Netapally AU - Pradep Kumar Yadav Allagadda AU - Venkatapuram Soujanya PY - 2025 DA - 2025/03/17 TI - Plant Health Condition Recognition Using Neural Network Smart Agriculture System BT - Proceedings of the International Conference on Advanced Materials, Manufacturing and Sustainable Development (ICAMMSD 2024) PB - Atlantis Press SP - 408 EP - 416 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-662-8_34 DO - 10.2991/978-94-6463-662-8_34 ID - Reddy2025 ER -