IIT Tirupati Navavishkar I-Hub Foundation Website
Last Date of Registration: 26 January 2026
A national-level innovation challenge focused on AI/ML-based geospatial solutions for Smart Rural Planning using drone datasets, supporting Digital Governance and Viksit Bharat 2047, jointly organised by the Geo-Intel Lab, IITTNiF, the Ministry of Panchayati Raj, and NIC Geospatial Division . This national-level initiative aims to advance geospatial intelligence using AI/ML, drone technologies, point-cloud analytics, and GIS engineering—bringing together students, researchers, startups, and domain experts.
Rural and semi-urban settlements in India continue to experience flooding, waterlogging, and inefficient drainage systems, primarily due to outdated infrastructure and limited spatial data.
The SVAMITVA Scheme, using drone-based mapping, CORS and GIS technology has successfully demonstrated the power of geospatial technology in village property demarcation and rural planning.
However, the full potential of drone imagery and AI/ML for automating hydrological modeling, drainage design, and spatial analysis remains largely untapped.
This challenge seeks to harness AI/ML algorithms to process high-resolution drone datasets, enabling rapid and scalable feature extraction, DTM creation, and drainage mapping.
The initiative supports India’s broader mission of promoting Digital Governance, Atmanirbhar Bharat, and Viksit Bharat 2047, by empowering innovators to create indigenous, data-driven solutions for rural and urban planning.
The Hackathon also provides a collaborative platform to connect students, researchers, startups, and domain experts, fostering innovation through applied learning.
Hands-on experience with real geospatial datasets
Skill development on AI/ML + GIS + Hydrological modelling
National exposure and recognition
Certificates, Attractive cash prizes
Opportunity for incubation at IITTNiF
Chance to collaborate with national geospatial agencies
Develop AI/ML-based feature extraction models capable of identifying key structures (buildings, roads, water bodies, utilities, etc.) from high-resolution drone orthophotos.
Create automated DTM and drainage network modeling workflows from point-cloud datasets, improving efficiency in hydrological design and land management.
Promote innovation and research collaboration among academia, industry, and government to strengthen India’s geospatial intelligence ecosystem.
Enhance the accuracy, scalability, and reliability of geospatial data processing for rural mapping and planning applications.
Encourage participants to develop open, interoperable, and scalable geospatial solutions that can be adapted across diverse Indian terrains.
The Hackathon Challenge offers participants a one-of-a-kind opportunity to work with real-world datasets, cutting-edge technologies, and nationally relevant problem statements in the fields of AI, Drone Mapping, and Geospatial Intelligence. Beyond competition, it is a platform for learning, collaboration, and innovation, aimed at nurturing the next generation of technology leaders and problem solvers.
Work directly with drone imagery, point-cloud data, and AI/ML models for feature extraction and terrain analysis.
Gain exposure to Digital Twin development, spatial analytics, and automation workflows used in modern infrastructure planning.
Learn practical methods to convert raw data into actionable insights for decision-making in real-world applications.
Strengthen your understanding of Geospatial Intelligence, AI/ML algorithms, and hydrological modeling.
Acquire industry-relevant skills in data processing, visualization, and predictive modeling, applicable across public and private sectors.
Build competencies that align with national priorities in Digital India, Smart Cities, and Gati Shakti initiatives.
Receive mentorship from domain experts, faculty, and industry leaders.
Learn best practices in data-driven research, AI deployment, and geospatial application design.
Gain professional insights into the future of geospatial technologies and AI integration.
Collaborate with interdisciplinary teams from academia, industry, and government organizations.
Expand your professional network through interactions with innovators, entrepreneurs, and technical experts in the field.
Discover opportunities for joint research, internships, and industry partnerships beyond the event.
Compete for certificates, cash prizes, and national-level recognition for innovative ideas and technical excellence.
Get featured in Geo-Intel Lab, IITTNiF’s outreach publications.
Exceptional teams may be invited to demonstrate their solutions at future national forums and conferences.
Promising ideas and prototypes will be evaluated for incubation under IITTNiF’s Startup and Innovation Program.
Access advanced laboratory infrastructure, mentorship, and potential funding to further develop and commercialize solutions.
Receive support in intellectual property (IP) creation, business model development, and pilot implementation.
Play a direct role in advancing India’s geospatial innovation ecosystem through technology that serves the public good.
To Contribute to national programs including SVAMITVA, Atmanirbhar Bharat, and Viksit Bharat 2047.
Join a movement that empowers innovators to apply technology for inclusive growth, sustainability, and better governance.
UG / PG / PhD Students
Researchers & Faculty
Startups & Industry Professionals
2–5 members per team
1. Problem Statement 1 : Feature Extraction from Drone Images:
i. Develop an AI model capable of identifying key features in orthophotos with high
precision. Use of AI/ML techniques for extraction of the following features from
SVAMITVA Drone Imagery: -
Building footprint extraction (built-up area from the drone image and classified roof-top based on observation of the imagery as RCC, Tiled, Tin, and Others.
Road feature extraction
Waterbodies extraction,
Distribution Transformer location/ Over-head Tank, well location identification etc.
ii. Achieve a target accuracy of 95% in feature identification.
iii. Optimize the model for efficient processing and deployment.
Input Data
Drone imagery for 10 villages (training & validation).
Drone imagery for 10 additional villages (output testing).
Expected Deliverables
SVAMITVA Scheme drone-images for 10 villages along with feature extracted datasets for 10 villages to train and validate the AI model, and 10 more villages drone data for output testing.
A fully trained and optimized AI model for feature identification in orthophotos.
Documentation detailing the model architecture, training process, and deployment guidelines.
A final report summarizing the project outcomes, including accuracy metrics and recommendations for future improvements.
2. Problem Statement 2: DTM Creation using AI/ML from point cloud data and development of drainage network
To conceptualize and develop a data-driven, DTM using Drone point cloud datasets leveraging AI/ML:
Delineate natural surface-water flow paths and low-lying zones,
Predict waterlogging hotspots, and
Design an optimized, resilient drainage network for densely inhabited village (abadi) areas.
Input data:
Point Cloud data for 10 villages
Expected Deliverables
Automated AI/ML Processing: From point-cloud classification to generate DTM.
Optimized Drainage Network Design: GIS-ready layers and design parameters.
Documentation detailing the model architecture, training process, and deployment guidelines.
A final report summarizing the project outcomes, including accuracy metrics and recommendations for future improvements.
Winner: ₹1,00,000
Runner-Up: ₹75,000
Merit Award: ₹50,000
Excellence Awards: ₹10,000 × 6 teams
Recognition Awards: ₹5,000 × 9 teams
Development of working prototypes or proof-of-concept models integrating AI/ML, Drones, and GIS.
Generation of AI-driven digital maps, DTMs, and decision-support systems for real-world applications.
Creation of an innovation ecosystem connecting academic research with industry needs.
Strengthening the foundation for digital governance and data-driven infrastructure planning.
Identification of talent and technology solutions for potential opportunities.