Village Weather Station Model
A community-driven and scalable model to aid farmers’ preparedness to counter crop failure and prevent hunger.
The project aims to target hunger and farmer’s distress due to changing and unpredictable climatic conditions.
India continues to be an agrarian economy, with 119 million farmers who make 25% of the total workforce, according to the Census data. But, worryingly, farmer suicides accounted for 7.4 per cent of the total deaths by suicide in India in 2019, as provided by the National Crime Records Bureau. In 2021 alone, erratic climate has led to the loss of 5 million hectares of crop in India.
In 2022, Maharashtra State Agriculture department reported the damaged crop area of over 800,000 hectares covering 24 districts due to incessant rains received in a single month. Hunger Watch-II survey revealed that 20 percent of total households in Maharashtra state face severe food shortage across 17 districts of Maharashtra.
Without the real time and accurate delivery of weather forecast information, local farmers are unable to take well-guided business decisions. Wrong decisions on this front often pushes them into further losses and debt due to crop damage, affecting food security and productivity of the crops in the region.
A weather station that predicts various relevant weather parameters for farmers using Artificial Intelligence by capturing real-time, local data and thus helping farmers take precautionary measures and make informed decisions about planning the crop cultivation cycle that is suitable to the existing weather conditions.
Currently, the solution serves local farmers in Maharashtra who face the wrath of unpredictable climate-related events every year. For lack of access to proper weather technology which is accurate and reliable, farmers often tend to end up losing their crops to extreme weather events, incur losses and fall behind on debt repayment, leading to farmer distress and deaths by suicide.
The solution aims to provide the farmers with the right information on weather and its patterns, helping them predict the right conditions for crop cultivation.
Majority of my teammates come from rural and underserved communities, including some who come from family of farmers. Our backgrounds gave us the opportunity to closely observe the challenges faced by our communities that have often been pushed to the margins. With our lived experiences, we now have the exclusive perspective that helps us ideate and design a solution that can cater to the farmers. We believe that problems like the ones faced by our farmers require low-cost, and innovative solutions. Moreover, our experience of volunteering with non-for-profit organisations have provided us with the exposure to grass-root realities and reinforced the need to provide solutions tailored to the needs of the communities. We have also acquired fundamental skills such as planning, problem solving, critical and creative thinking which can bolster our objective to actualize the solution on the ground.
We have conducted user need analysis including empathy mapping with our primary stakeholders to best understand their primary needs and draw out the root causes to the problem. Our product is designed to provide solutions to the pain points of farmers, which is lack of well-informed data points pertaining to dynamic weather events. We have also worked closely with the Pi Jam foundation, whose innovative interventions have supported us to enhance our solution prototype. We have also conducted FGDs with farmers and learnt from their feedback which has helped us improve our prototype further.
- Taking action to combat climate change and its impacts (Sustainability)
- Prototype: A venture or organization building and testing its product, service, or business model
Our solution takes an innovative approach to solve an old problem that was born out of lack of sufficient and reliable data for local farmers.
Instead of relying on external and more generalized data alone, the whole process of setting up and managing a village weather station will be done by village school students as a part of their extra curricular project which will aid in the development of their foundational skills - problem solving and computational thinking along with digital learning (highly relevant in today’s work economy). The idea is to build a publicly owned asset by the village people.
Our approach not only caters to the farmer’s issue but also targets SDG 4 (quality education), a persisting concern in remote and rural parts of the country. Also, the solution not only aids farmers in taking precautionary steps but also take proactive measures in sowing the right kind of crop at right time, owing to the prevalent weather conditions.
We do expect the weather station to become a reliable source of data for farmers to educatedly lean on, along with their traditional wisdom.
To increase the income of farmers by cutting down losses from crop failure
Educate 100% of the villages in Ambegaon district in Maharashtra about the need and utility of a weather station and utilization of the data received from it.
10% of rural villages in Maharashtra have their own village weather station
It is made using several sensors . There is a BMP 180 sensor ( barometric pressure sensor) which calculates pressure, DHT 22 sensor (digital humidity temperature sensor) which calculates humidity and temperature, an LDR which calculates the light intensity, an anemometer which calculates the wind speed, wind vane for wind directions, a rain gauge which calculates the amount of rainfall, and a breadboard several jumper wires along with open source Rasberry Pi.
Once it starts working the sensors and hardware calculate their specified atmospheric data and send it to pi. The pi is connected to a PC. It shows these values on the screen and using the program we have written into the software it tells you the weather forecast.
- Artificial Intelligence / Machine Learning
- Big Data
- India
Currently served - 0
Next Year’s projected impact number - 1,813 people in Thorandale village, dist. Pune, State Maharashtra, India
Some of the implementation barriers my team has faced include:
Educating and building trust among farmers to make well-informed data and evidence-based decisions in the agriculture business over following traditional subjective practices
Administrative hurdles in incorporating weather station project and its management in government schools’ extracurricular activities
Gram Panchayat at village level- Partnering for data sharing to
-make local agriculture policy decisions
-enhance farmers’ income and reduce losses
Local farmer and producer organizations - to spread awareness and pushing adoption of best practices
Rural school students-led weather station drills into weather data collected real time and identifies local weather patterns and fluctuations. This information is usable and valuable for the farmer to make informed decisions; take precautionary steps with regard to the upcoming crop cycle. Infact, the more reliable this data is, the more it can help farmers do short to medium term crop planning-what crops to sow; which ones to combine for multiple cropping; choice of crops based on the type of weather events expected, like whether it is likely to be dry or will there be plenty of rains and when. The farmers will be provided information about best practices through the use of animated videos in vernacular language and pictorial pamphlets. Community sessions and gatherings for discussion on the need and use of intervention among the farming community and showcasing of demonstrated impact during pilot phase at common village public hotspots.
The school students who manage their village weather station have various avenues to market the data for the end user which is the farmer community, policymakers or government agencies formulating policies to benefit the farming community. The data can be sold to for-profit agencies on a subscription basis. Innovation grants and utilizing finances secured from applicable government schemes is another avenue for funding. After experiencing consistent income growth by farmers, the farmer’s may be persuaded to pay a small percent of their income for the data and clear recommendations for next crop and ideal sowing and harvesting time. The revenue can be put to use for village development activities in collaboration with government bodies.
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