Agriculture helper module
- detect humidity, sunlight, day or night and control water accordingly (a)
- can be set for different crops (m)
- can be for different seasons (m)
- can be connected to ultrasonic pest repelling devices (m)
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Jai - RA2212701010011
Hemant - RA2212701010010
Lakshay - RA2212701010051
Saptarishi - RA2212701010035
Sparsh - RA2212701010005
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FarmaTech : Smart and Sustainable Crop Monitoring System with Raspberry Pi
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Abstract : FarmaTech is an innovative project that introduces a Smart and Sustainable Crop Monitoring System powered by Raspberry Pi. This system combines cutting-edge technology with agricultural practices, enabling farmers to remotely monitor and manage their crops. With real-time data collection of crucial factors like soil moisture, temperature, and humidity, FarmaTech empowers farmers to make informed decisions, optimize resource usage, and promote sustainable farming practices. By integrating the capabilities of Raspberry Pi, this solution aims to enhance crop yields, conserve resources, and contribute to a greener and more efficient agricultural landscape.
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Objective : To create FarmaTech, a sophisticated Smart Crop Monitoring System, by harnessing the capabilities of Raspberry Pi. This system will revolutionize agriculture by providing real-time data collection, advanced image analysis, and environmental sensing. Through seamless integration, FarmaTech aims to empower farmers with precise insights for informed decision-making, optimizing resource allocation, and boosting overall agricultural productivity. The system's innovative approach to crop monitoring holds the potential to transform traditional farming practices into technologically advanced, efficient, and sustainable processes. FarmaTech envisions a future where cutting-edge technology converges with agriculture, ensuring food security and economic prosperity.
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Future prospect :
Machine Learning and AI Integration: As your system collects more data over time, consider implementing machine learning algorithms to analyze the data and provide predictive insights. AI models could help in detecting disease patterns, predicting crop yields, and recommending optimal irrigation and fertilization strategies.
Remote Sensing and Drone Integration: Integrating remote sensing technologies and drones could enhance the system's capabilities. Drones can capture high-resolution imagery of crops, which can then be processed to monitor plant health and identify areas of concern.
Weather Forecast Integration: Incorporating real-time weather data and forecasts into your system could help farmers make informed decisions about when to plant, irrigate, and protect their crops from extreme weather conditions.
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UPDATE: