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Connected agricultural intelligence

From Soil
to Sky

See agriculture through connected ground, crop, aerial and satellite intelligence.

01

GROUND

IoT soil sensing

02

CROP

Computer vision assessment

03

AIR

Drone multispectral imaging

04

SKY

Satellite remote sensing

SKYSatellite remote sensingAIRDrone & multispectral imagingGROUNDIoT soil intelligence

01 · UNDERGROUND

Ground Intelligence

Sensors placed in the root zone report soil conditions continuously, supporting early detection of nutrient deficiencies and in-situ environmental monitoring rather than after-the-fact diagnosis.

Soil Moisture

Soil Temperature

pH

NPK

EC

Salinity

MoisturemeasuredTemperaturemeasuredpHmeasuredNPKmeasuredECmeasuredSalinitymeasured

02 · CROP CANOPY

Crop Intelligence

Above the soil, the crop itself carries the signal. Computer vision reads the canopy and, combined with ground data, turns visual evidence into an assessment of how the crop is doing.

Crop Health
Canopy condition assessed from field imagery.
Computer Vision
Visual analysis of leaves, canopy and crop structure.
Pattern Recognition
Repeating signals identified across the plot over time.
Field Signals
Image evidence combined with ground sensor context.
Crop canopy viewed for computer-vision health analysis
CROP IMAGE→AI ANALYSIS→CROP SIGNAL

03 · AIR

Aerial Intelligence

A drone pass converts a field into a sequence of interpretable layers: multispectral capture, NDVI, chlorophyll analysis, crop health mapping and yield outlook — the same field, progressively better understood.

Aerial view of Indian agricultural plots used for crop monitoring

Illustrative aerial intelligence layer

01

Field image

02

Multispectral

03

NDVI

04

Chlorophyll

05

Health map

06

Yield outlook

04 · SKY

Satellite Intelligence

The view widens from a single plant to a landscape. Remote sensing places one field in the context of the wider growing area, its vegetation trends and how land around it is used.

Plant

Individual crop signal

Field

One managed plot

Multiple fields

Cluster-level patterns

Landscape

Large-area observation

Remote Sensing

Observation of vegetation and land beyond one plot.

Climate Impact Assessment

Longer-term climatic influence on the growing area.

Vegetation Trends

Directional change in vegetation across seasons.

Land-use Monitoring

How land in the area is being used and changing.

Connected Agricultural View

Ground sensing, crop imagery, drone intelligence and satellite observation come together in MeriSristi.

  1. GROUND

    IoT soil sensing

  2. CROP

    Computer vision

  3. AIR

    Drone / multispectral

  4. SKY

    Remote sensing

  5. MERISRISTI

    Connected agricultural intelligence

SENSE→SEE→UNDERSTAND→PREDICT→ACT
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