“Each daybreak, I might wake with a knot in my chest, questioning if the soil beneath my ft would already be dry, if the pumps I fired up have been burning diesel for nothing, or if my crops would wilt earlier than rain got here. I used to be by no means sure. I spent extra hours guessing than tending.”

That’s how Ramesh Chandra Dahiya of Mandaura, Sonipat, remembers his life earlier than the Resolution Help System (DSS) developed by Sharanya Mehta. Seasons of uncertainty, diesel burnt in useless, and crops harassed by drought or flood had turn into all too acquainted. However they have been about to alter.

From cracked soil to curiosity

The inspiration traces again to Sharanya’s childhood. Rising up, she spent many summers in Alwar, visiting villages together with her grandfather. She noticed soil bake beneath the solar, fissures spreading throughout dry land, and crops wilting or drowning relying on how water was utilized—typically by custom, typically by intuition, typically by hope that rain would possibly rescue the day.

“When pumps ran for hours however roots stayed dry, or when darkish clouds gathered solely to move with out rain, I saved questioning—was there a strategy to measure, to foretell, to information farmers higher? I started considering of how one can make the method simpler, in order that their effort wouldn’t go to waste and their crops wouldn’t endure needlessly,” she tells The Higher India.

Her first experiments got here by way of the Rotary Membership of Delhi Premier (RCDP) and her personal initiative, Venture Jal, which she based in Class 9. She studied verify dams—their shapes, angles, and supplies—and the way a lot water they retained. Her work wasn’t simply theoretical; she additionally spoke with farmers and noticed what options they have been in search of.

“Once I noticed roots wilting despite the fact that the floor regarded moist, I realised no quantity of water-harvesting buildings alone might shield these crops,” says the 17-year-old. “We would have liked one thing that spoke each to the soil and the sky.”

From thought to route

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

“Once I first met her, she was talking passionately about water harvesting and water utilization. Her power, readability, and insistence that instruments should not solely be right however usable struck me instantly,” he says.

He turned her mentor, and collectively they formed the concept.

“I guided her to assemble agronomy datasets—what every crop wants at every stage, how soil texture and depth have an effect on moisture, and the way climate forecasts ought to modulate irrigation timing. She was clear from the start that user-friendliness, with voice prompts, native languages, and offline entry, could be central to the DSS,” he provides.

“I didn’t need the app to simply say when to water,” Sharanya explains. “It has to inform how a lot, the place, and why—like recommendation you possibly can belief.”

Assembling the system: Knowledge, sensors, and satellites

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

The system’s spine contains sensors (LoRa/Wi-Fi enabled capacitive and TDR-based) positioned at two depths (0–30 cm and 30–60 cm); satellite tv for pc knowledge utilizing NDMI (Normalised Distinction Moisture Index) from ISRO Bhuvan and Sentinel-2; climate forecasts (rainfall, temperature, wind, evapotranspiration); and backend processing on cloud servers (AWS/Azure) with pipelines in Python and Node.js.

Sharanya emphasises, “We made each characteristic solely after farmers requested for it. We included color maps, voice prompts, and easy icons to stop any confusion.”
The app interface exhibits colour-coded maps so farmers can see moisture zones at a look, two-week schedules, alerts, and voice and video guides. It helps a number of native languages similar to Hindi, Tamil, and Marathi, and works offline when the community fails.

From idea to discipline

Sharanya’s journey by way of 2025 unfolded in levels:

• January–March: She visited Mandaura, Sonipat, typically, assembly farmers like Ramesh, Jagvir Singh, and Ram Parmar. She mapped their struggles—empty wells, cracked soil, wasted diesel—and sketched early app designs.
• April–Could: Sensors have been chosen, satellite tv for pc API integrations established, and backend growth started. Soil samples from pilot plots have been used to fine-tune calibration. Farmers examined app mock-ups, preferring easy icons, native languages, and offline entry.
• June: Sensors have been totally deployed, and dwell knowledge began flowing. Farmers started utilizing early app variations to enter soil profiles, choose crops, and look at tailor-made irrigation schedules. Suggestions prompted refinements for readability and value.
• July: The system underwent rigorous lab testing—sensors have been uncovered to excessive warmth, mud, and humidity. Soil moisture readings have been benchmarked in opposition to NDMI knowledge. The app’s visuals and layouts have been refined additional. Vizexec Transformation in Gurgaon validated the software program structure, whereas Loyli Engineering Options in Pune developed and examined a pump controller to automate irrigation.
• August: Full-scale discipline trials started in Mandaura. Farmers registered fields, adopted schedules, and responded to alerts. Water use dropped, and crops improved. On 19 August, Sharanya obtained the celebrated CREST Gold Award. That very same month, she filed and secured a provisional patent for the DSS, overlaying its decision-making engine, real-time knowledge integrations, and voice-enabled, multilingual interface.

“This was probably the most thrilling phases. The pump controller checks confirmed the DSS might talk instantly with irrigation {hardware}, decreasing each labour and gasoline,” she says.

How the DSS guides farmers

The Resolution Help System works by way of three phases:

• Knowledge assortment: Soil sensors file moisture at two depths hourly; NDMI satellite tv for pc readings spotlight moisture stress zones; climate forecasts predict rainfall, wind, and evaporation; farmers enter crop sort, sowing date, and soil profile.
• Evaluation and resolution engine: Cloud-based logic (Python, Node.js on AWS/Azure) combines knowledge, matches it with agronomic guidelines, and calculates when and the way a lot to irrigate. Updates occur in actual time.
• Recommendation supply: A cell app delivers colour-coded maps, schedules, alerts, voice prompts, and video guides in native languages. The app caches directions for offline use. The place pump controllers are put in, alerts automate irrigation, saving water and gasoline.

“Each time a farmer opens the app, I would like them to really feel they’re their very own discipline—not simply knowledge, however steering they consider in,” Sharanya says.

Voices from the soil

Ramesh Chandra shares: “One morning, I noticed soil moisture additional down was good, although the floor felt dry. The app stated I might skip watering, and I did. By noon, crops regarded more healthy, and I used far much less diesel. I used to dread dry spells; now I verify the app as a substitute of guessing.”

Jagvir Singh, who grows wheat, mustard, and bajra, says: “Beforehand, I relied on how the soil regarded, or whether or not it cracked at midday. The forecast would possibly lie, or rain would possibly shock me. Now, seeing maps, checking sensor readings, and listening to voice prompts telling me to water frivolously or in no way, I consider extra in doing much less when it’s right, slightly than doing extra simply in case.”

Ram Parmar provides, “My pumping schedule was inflexible, it doesn’t matter what the soil stated. Now I comply with the DSS; typically I don’t pump these mounted hours, typically I water frivolously. That flexibility means I spend much less, my labour is much less frantic, and harvests really feel steadier.”

Why this innovation issues

India is going through growing water stress, pushed by local weather change, over-extraction of groundwater, and inefficiencies in water use. The Composite Water Administration Index by NITI Aayog highlights that over 83% of India’s water is consumed by agriculture, and warns that with out pressing enhancements in irrigation effectivity, the nation faces a extreme water disaster.

Sharanya’s DSS addresses these gaps instantly. It’s data-driven, user-friendly, cost-sensitive, and designed for actual rural situations. In villages, dawns are shifting. Farmers like Ramesh now not start their day with dread. They pause, verify the app, see moisture ranges and forecasts, and comply with guided schedules.

All footage courtesy Sharanya Mehta