Class 12 Student’s Smart Irrigation App Helps Farmers Save Water, Diesel & Crops

“Every dawn, I would wake with a knot in my chest, wondering if the soil beneath my feet would already be dry, if the pumps I fired up were burning diesel for nothing, or if my crops would wilt before rain came. I was never certain. I spent more hours guessing than tending.”

That is how Ramesh Chandra Dahiya of Mandaura, Sonipat, remembers his life before the Decision Support System (DSS) developed by Sharanya Mehta. Seasons of uncertainty, diesel burnt in vain, and crops stressed by drought or flood had become all too familiar. But they were about to change.

From cracked soil to curiosity

The inspiration traces back to Sharanya’s childhood. Growing up, she spent many summers in Alwar, visiting villages with her grandfather. She saw soil bake under the sun, fissures spreading across dry land, and plants wilting or drowning depending on how water was applied—sometimes by tradition, sometimes by instinct, sometimes by hope that rain might rescue the day.

“When pumps ran for hours but roots stayed dry, or when dark clouds gathered only to pass without rain, I kept wondering—was there a way to measure, to predict, to guide farmers better? I began thinking of how to make the process easier, so that their effort would not go to waste and their crops would not suffer needlessly,” she tells The Better India.

Her first experiments came through the Rotary Club of Delhi Premier (RCDP) and her own initiative, Project Jal, which she founded in Class 9. She studied check dams—their shapes, angles, and materials—and how much water they retained. Her work wasn’t just theoretical; she also spoke with farmers and observed what solutions they were looking for.

“When I saw roots wilting even though the surface looked moist, I realised no amount of water-harvesting structures alone could protect those plants,” says the 17-year-old. “We needed something that spoke both to the soil and the sky.”

From idea to direction

Sharanya met Commodore Sridhar Kotra, a military veteran, engineer, and co-founder of Agrimatrix India Pvt Ltd—a centre bringing agricultural technologies to village clusters—during her RCDP work.

“When I first met her, she was speaking passionately about water harvesting and water usage. Her energy, clarity, and insistence that tools must not only be correct but usable struck me immediately,” he says.

He became her mentor, and together they shaped the idea.

“I guided her to assemble agronomy datasets—what each crop needs at each stage, how soil texture and depth affect moisture, and how weather forecasts should modulate irrigation timing. She was clear from the beginning that user-friendliness, with voice prompts, local languages, and offline access, would be central to the DSS,” he adds.

“I did not want the app to just say when to water,” Sharanya explains. “It has to tell how much, where, and why—like advice you can trust.”

Assembling the system: Data, sensors, and satellites

By early 2025, now in Class 12, Sharanya’s project had matured from blueprints into working models.

The system’s backbone includes sensors (LoRa/Wi-Fi enabled capacitive and TDR-based) placed at two depths (0–30 cm and 30–60 cm); satellite data using NDMI (Normalised Difference Moisture Index) from ISRO Bhuvan and Sentinel-2; weather forecasts (rainfall, temperature, wind, evapotranspiration); and backend processing on cloud servers (AWS/Azure) with pipelines in Python and Node.js.

Sharanya emphasises, “We made every feature only after farmers asked for it. We included colour maps, voice prompts, and simple icons to prevent any confusion.”
The app interface shows colour-coded maps so farmers can see moisture zones at a glance, two-week schedules, alerts, and voice and video guides. It supports multiple local languages such as Hindi, Tamil, and Marathi, and works offline when the network fails.

From concept to field

Sharanya’s journey through 2025 unfolded in stages:

• January–March: She visited Mandaura, Sonipat, often, meeting farmers like Ramesh, Jagvir Singh, and Ram Parmar. She mapped their struggles—empty wells, cracked soil, wasted diesel—and sketched early app designs.
  
  
• April–May: Sensors were chosen, satellite API integrations established, and backend development began. Soil samples from pilot plots were used to fine-tune calibration. Farmers tested app mock-ups, preferring simple icons, local languages, and offline access.
  
  
• June: Sensors were fully deployed, and live data started flowing. Farmers began using early app versions to enter soil profiles, select crops, and view tailored irrigation schedules. Feedback prompted refinements for clarity and usability.
  
  
• July: The system underwent rigorous lab testing—sensors were exposed to extreme heat, dust, and humidity. Soil moisture readings were benchmarked against NDMI data. The app’s visuals and layouts were refined further. Vizexec Transformation in Gurgaon validated the software architecture, while Loyli Engineering Solutions in Pune developed and tested a pump controller to automate irrigation.
  
  
• August: Full-scale field trials began in Mandaura. Farmers registered fields, followed schedules, and responded to alerts. Water use dropped, and crops improved. On 19 August, Sharanya received the prestigious CREST Gold Award. That same month, she filed and secured a provisional patent for the DSS, covering its decision-making engine, real-time data integrations, and voice-enabled, multilingual interface.

“This was one of the most exciting phases. The pump controller tests showed the DSS could communicate directly with irrigation hardware, reducing both labour and fuel,” she says.

How the DSS guides farmers

The Decision Support System works through three phases:

• Data collection: Soil sensors record moisture at two depths hourly; NDMI satellite readings highlight moisture stress zones; weather forecasts predict rainfall, wind, and evaporation; farmers input crop type, sowing date, and soil profile.
• Analysis and decision engine: Cloud-based logic (Python, Node.js on AWS/Azure) combines data, matches it with agronomic rules, and calculates when and how much to irrigate. Updates happen in real time.
• Advice delivery: A mobile app delivers colour-coded maps, schedules, alerts, voice prompts, and video guides in local languages. The app caches instructions for offline use. Where pump controllers are installed, signals automate irrigation, saving water and fuel.

“Every time a farmer opens the app, I want them to feel they are looking at their own field—not just data, but guidance they believe in,” Sharanya says.

Voices from the soil

Ramesh Chandra shares: “One morning, I saw soil moisture further down was good, though the surface felt dry. The app said I could skip watering, and I did. By midday, plants looked healthier, and I used far less diesel. I used to dread dry spells; now I check the app instead of guessing.”

Jagvir Singh, who grows wheat, mustard, and bajra, says: “Previously, I relied on how the soil looked, or whether it cracked at noon. The forecast might lie, or rain might surprise me. Now, seeing maps, checking sensor readings, and hearing voice prompts telling me to water lightly or not at all, I believe more in doing less when it is correct, rather than doing more just in case.”

Ram Parmar adds, “My pumping schedule used to be rigid, no matter what the soil said. Now I follow the DSS; sometimes I don’t pump those fixed hours, sometimes I water lightly. That flexibility means I spend less, my labour is less frantic, and harvests feel steadier.”

Why this innovation matters

India is facing increasing water stress, driven by climate change, over-extraction of groundwater, and inefficiencies in water use. The Composite Water Management Index by NITI Aayog highlights that over 83% of India’s water is consumed by agriculture, and warns that without urgent improvements in irrigation efficiency, the nation faces a severe water crisis.

Sharanya’s DSS addresses these gaps directly. It is data-driven, user-friendly, cost-sensitive, and designed for real rural conditions. In villages, dawns are shifting. Farmers like Ramesh no longer begin their day with dread. They pause, check the app, see moisture levels and forecasts, and follow guided schedules.

All pictures courtesy Sharanya Mehta