Project Drishti: Building a Smarter Indore
An AI-powered integrated system to monitor, predict, and prevent illegal construction, ensuring sustainable and planned urban development.
The Urban Growth Dilemma
As Indore expands, it faces critical challenges that hinder planned development. This section outlines the core problems that Project Drishti is designed to solve, transforming inefficiencies into streamlined, technology-driven processes.
Delayed Detection
Manual surveys are infrequent and slow, allowing illegal constructions to complete before authorities can intervene.
Siloed Departments
Poor coordination between IMC, T&CP, and Nazul leads to data gaps, enforcement delays, and lack of accountability.
Lack of Predictive Insight
Reactive enforcement misses the opportunity to proactively monitor high-risk zones before violations occur.
Manual Loopholes
Paper-based approval and inspection processes are prone to errors, manipulation, and significant delays.
No Real-time Monitoring
Absence of a live, city-wide view of construction activity prevents immediate response and strategic planning.
Limited Citizen Integration
Public complaints are often lost in bureaucracy, lacking a transparent tracking and resolution mechanism.
The Drishti Ecosystem
Project Drishti is not just a single tool, but a complete, interconnected ecosystem. This interactive diagram shows how data flows from various sources, is processed by our AI engine, and empowers different users through dedicated applications. Hover over any component to learn its role.
1. Data Acquisition
2. AI Core Engine
3. User Applications
Inside the Engine
The system's power lies in its specialized modules working in harmony. Each component has a distinct role, from data collection to citizen empowerment. Use the tabs below to explore the technology and function of each part of the Drishti ecosystem.
The Brain: AI & Machine Learning Core
This is where raw data is turned into actionable intelligence. The AI Core automates the most labor-intensive part of monitoring, working 24/7 to keep a digital eye on the city.
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Spatial Change Detection: Using computer vision, the AI compares new satellite/drone images against the baseline GIS map to instantly flag any physical changes—a new foundation, an extra floor, or a new boundary wall.
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ML Classification: Once a change is detected, a machine learning model classifies its nature (e.g., 'Permanent Building', 'Temporary Shed', 'Excavation'), which helps prioritize the alerts for officials.
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Predictive Analytics: By analyzing historical violation data, the system identifies future "hotspots"—areas with a high probability of illegal construction. This allows for proactive surveillance and prevention.
Drishti in Action: A Pilot Case Study
Theory is one thing, but real-world impact is what matters. This interactive timeline walks you through a typical case, demonstrating how Project Drishti drastically shortens the response time from months to mere hours.
✨ Strategic Command Center
Move beyond reaction to proactive planning. Use Gemini as an AI Urban Planning Analyst to synthesize data, identify trends, and formulate strategies for Indore's future growth.
Ask Your AI Analyst:
Select a strategic query to see how Gemini can provide high-level insights based on system data.
Generating strategic insights with Gemini...
Transformative Impact
By shifting from a reactive, manual process to a proactive, automated system, Project Drishti delivers tangible benefits for the city, its administration, and its citizens. The chart below provides a stark visual contrast of the efficiency gains.
📈 Scalability & Cost-Effectiveness
Designed for growth, the system can be piloted in one zone and expanded city-wide. The cloud-based, pay-as-you-go model minimizes initial capital expenditure, while the long-term ROI from plugged revenue leakages and reduced operational costs is substantial.
🤝 Transparency & Accountability
With digital audit trails for every case and a transparent complaint tracking system for citizens, Drishti fosters a culture of accountability. Data-driven reports highlight performance and ensure that actions are taken and tracked from start to finish.