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PS 26128SOFTWAREAgriculture, FoodTech & Rural DevelopmentFast Prototype (36h)

Efficient systems for early detection,prevention,and management of livestock diseases and animal health issues

Government Of MaharashtraMaharashtra State Innovation Society, Department of Skills, Employment, Entrepreneurship and Innovation
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30-Second Plain English Summary

Rural livestock farmers in Maharashtra suffer massive economic losses from infectious cattle and goat disease outbreaks (Lumpy Skin Disease, Foot-and-Mouth Disease, Peste des Petits Ruminants) that spread rapidly between villages before district veterinary officers are alerted. Build an AI-driven Livestock Epidemic Early Warning, Tele-Veterinary Diagnosis, and Outbreak Surveillance Platform for the Government of Maharashtra that uses smartphone computer vision to detect early skin lesions and spatio-temporal clustering to contain disease outbreaks.

5-Dimension Strategic ScorecardOverall Score: 4 / 5.0
Innovation
4 / 5
36h Feasibility
4.4 / 5
Uniqueness
4 / 5
Jury Appeal
4.2 / 5
Tech Depth
3.6 / 5
Recommended System Architecture Pipeline
Farmer Animal Photo (WhatsApp/PWA) -> Veterinary Vision AI (YOLOv8) -> Spatial Epidemic Cluster Engine (SaTScan) -> PostGIS Containment Layer -> Maharashtra Animal Husbandry Dashboard
Recommended Tech StackClick to search similar
Official Government Problem Description
• Problem Description Livestock owners, field veterinarians,para-veterinary workers and government departments often lack a unified, realtime mechanism to identify emerging animal-health risks at the village, block and district levels. Disease symptoms may be reported late, diagnostic facilities may be distant, vaccination and treatment histories may be incomplete, and information from farms, veterinary dispensaries, laboratories, vaccination drives and surveillance programmes may remain fragmented. These gaps can delay containment, increase livestock mortality and productivity loss, raise the risk of zoonotic transmission, and affect farmers' incomes. The challenge is to create a practical system that enables early warning, rapid reporting, risk assessment, preventive action, referral and coordinated response, including in low-connectivity areas. • Expected Solution / Outcome A scalable animal-health surveillance and decision-support solution that can: capture symptom and mortality reports from farmers and field workers; use rulebased or AI-assisted triage to flag suspected outbreaks; integrate geospatial risk mapping, weather and historical disease trends; maintain animal-level or herd-level health,vaccination and treatment records; issue multilingual advisories and alerts; support sample collection, laboratory referral and case escalation; provide dashboards for veterinary officials; and operate through mobile, web, IVR or offline-enabled channels. Expected outcomes include reduced reporting time, earlier outbreak identification, improved vaccination coverage, faster treatment and containment, lower mortality and productivity loss, and stronger evidence-based planning.
AI & PPT Citation Format

Smart India Hackathon 2026 Problem Statement PS-26128: "Efficient systems for early detection,prevention,and management of livestock diseases and animal health issues", Ministry: Government Of Maharashtra. Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26128)

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