SWAMA — Smart Waste Monitoring & Automation
The Operating System for Modern Waste Management
The Problem
Urban waste management fails not because cities lack vehicles or manpower — it fails because operations are opaque, fragmented, and hard to enforce.
Common systemic issues include:
- Missed or partial collections with no verifiable proof
- Route deviations and inefficient fleet movement
- Contractor non-compliance and weak accountability
- Manual reporting, delayed audits, and reactive enforcement
- Poor citizen experience and low trust
Most systems provide visibility after failure. SWAMA is designed to prevent failure by design.
Platform Overview
SWAMA is an AI-driven governance platform that unifies:
- GPS & telematics data from vehicles
- IoT sensors (where available)
- Mobile workflows for field staff
- Administrative dashboards for city and state authorities
into a single operational intelligence layer.
It operates continuously — at street, ward, zone, and city level — enabling real-time monitoring, automated detection of violations, and data-backed decision-making.
AI Models Powering SWAMA
Route Optimization Intelligence
AI-driven routing that dynamically adapts to:
- Service zones and ward boundaries
- Vehicle capacities and types
- Time windows and shift constraints
- On-ground disruptions and delays
This replaces static route plans with living operational routes.
Missed Pickup Detection
Machine learning models correlate:
- GPS movement
- Stop duration
- Route completion patterns
to automatically detect missed households, partial coverage, and repeated service gaps — without manual verification.
Geo-fencing & Zone Violation Detection
AI continuously evaluates vehicle behaviour against:
- Assigned wards and routes
- Authorized dumping points
- Time-bound movement constraints
Flagging violations instantly, not during audits weeks later.
Attendance & Productivity Inference
Instead of manual attendance registers, SWAMA infers:
- Actual working hours
- Coverage achieved per shift
- Productivity at individual, crew, and contractor level
using movement, activity, and task completion signals.
Outcomes Delivered
SWAMA is measured by outcomes, not features.
Deployment Models
SWAMA is designed for government realities, not ideal conditions.
Deployment options include on-premise, state data centers, or cloud — aligned with policy and security requirements.
Case Snapshots
(Representative examples – details shared during engagement)
- City-wide deployment covering door-to-door collection and transportation
- AI-based route optimization reducing redundant travel
- Automated detection of missed routes and non-compliance
- Real-time dashboards for municipal leadership
