AI Solutions
We harness the power of Artificial Intelligence to solve real-world challenges across industries and sectors.
Smart Public Safety and Emergency Response System
Introduction: Urban environments face escalating challenges related to crime, emergency response delays, and public safety threats. Implementing a Smart Public Safety and Emergency Response System will transform urban safety by combining AI, IoT, and centralized communication. The proposed model ensures a safer city, optimizes resources, and empowers authorities and citizens alike for a resilient, future-ready public safety framework.
Objectives
Enhance public safety
Reduce crime rates
Optimize resources
Foster transparency
Citizen engagement
Key Components
AI-Powered Surveillance
IoT-Enabled Sensors
Integrated Command & Control Center
Geospatial and GPS Integration
Cyber security Framework
Disaster Early Warning
Smart Waste Management System
Introduction: Rapid urbanization has heightened the need for efficient and sustainable waste management in cities. Traditional waste collection methods often result in overflowing bins, inefficient routes, and increased operational costs. To address these challenges, a Smart Waste Management System utilizing IoT sensors, advanced analytics, and data-driven operations is proposed for modern urban environments.
Objectives
Enhance collection efficiency
Reduce operational costs
Improve urban cleanliness
Enable data-driven decisions
Promote environmental sustainability
Key Components
Sensor-Enabled Smart Bins
Route Optimization
Central Monitoring Platform
Analytics & Reporting
Citizen Engagement
Automatic Challan Generation for Overloaded and Over-Sized Vehicles
Introduction: Overloading and over-sizing of vehicles are major causes of road infrastructure deterioration, safety hazards, and revenue leakage. To address these challenges, we propose an advanced, automated system for real-time detection and automatic challan generation for overloaded and over-sized vehicles using a combination of AI, sensor technologies, and real time analytics to improve compliance, road safety, and administrative efficiency.
Objectives
Automate detection and penalization process
Enhance transparency and operational efficiency
Improve road safety
Protect infrastructure
Enable data-driven decision-making
Key Components
AI-Powered Surveillance
IoT-Enabled Sensors
Integrated Command & Control Cente
Geospatial and GPS Integration
Cyber security Framework
Disaster Early Warning
AI-Driven Transformer Health Monitoring and Failure Prediction System
Introduction: Presently, transformer health monitoring relies heavily on Dissolved Gas Analysis (DGA) sampling data. By introducing a novel AI-driven time series forecasting approach, it has an ability to interpret DGA gas values between irregular sampling intervals, providing insights at finer time resolutions (e.g., weekly or daily). Predicts potential breaches of threshold values, enabling proactive fault prediction and maintenance scheduling.
Objectives
Predictive Maintenance
Early Warning System
Transformer Health Indexing
Gases Progression between two sampling intervals
Key Components
Integrated Dashboard
Transformer Failure Forecasting
Threshold Breach Alerts
Downloadable Reports
Historic Data Visualization
> Disaster Early Warning