Page 211 - AI for Good-Innovate for Impact Final Report 2024
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AI for Good-Innovate for Impact



               49�2� Use case description


               49�2�1� Description


               Local farmers often rely on weather forecasts provided by national meteorological agencies,          49-CSIR-INSTI
               which typically offer generalized predictions for wide geographical areas without specific details
               tailored to local farmlands [1]. This limitation frequently results in local farmers experiencing
               losses due to inaccurate environmental condition predictions. To address this challenge
               effectively, there is a critical need for affordable weather stations deployed directly on local
               farmlands. These stations would enable precise and localized forecasting of environmental
               conditions essential for optimizing agricultural practices and minimizing risk.

               An AI-enabled soil analysis and weather station represents a transformative solution for local
               farmers, empowering them to monitor crucial soil and weather parameters with unprecedented
               accuracy and immediacy[1]. Leveraging advanced AI technologies, these weather stations
               operate without mechanical parts, capturing real-time data on rainfall intensity, wind direction
               and intensity, temperature, humidity, pressure, and air quality. Simultaneously, they conduct
               real-time soil analyses to measure temperature, humidity, pH levels, NPK content, and
               conductivity. The collected data is then visualized through intuitive dashboards accessible via
               smartphone apps and web browsers. Over time, this data will facilitate the development of
               predictive models tailored specifically to local farming conditions, ensuring informed decision-
               making and sustainable agricultural practices.

               UN Goals:

               •    SDG 1: No Poverty
               •    SDG 13: Climate Action

               Justification of UN Golas: SDG 1 (No Poverty): Local farmers are usually poor because most
               depend solely on selling their crop yields for money. The accurate predictive capabilities of
               the AI-enabled soil analysis and weather station will enable farmers to plan the planting and
               cultivation of their crops to increase yield. SDG 13 (Climate Action): Collecting and analyzing
               data from various individual farmlands across the country will help visualize the damage climate
               change has on farmlands and ensure that measures are taken to combat it. 


               49�2�2� Future work

               Our future work includes several important steps: data collection, proof of concept development,
               model development, and setting up reference tools, notebooks, and a simulation environment.

               The next steps will involve placing various environmental and soil analysis sensors on individual
               farmlands to collect data if scholarships and resources are given. This data will be sent wirelessly
               to a central system for live dashboards and predictive model development. Mobile apps and
               web servers will be created to test the proof of concept, ensuring that the collected data is
               accessible and useful for local farmers.


               49�2� Use case Requirement

               •    REQ-01: It is critical that the system collects real-time data on environmental conditions
                    and soil parameters from individual farmlands.





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