SustainLabs

Inspiration

The project was inspired by the urgent need for Sustainable AI & Green Tech within the telecommunications sector. With the rollout of 5G expected to triple energy demands and electricity prices rising, telecom operators face immense pressure to reduce operational costs and meet government Net Zero 2070 mandates. We saw an opportunity to replace outdated, reactive monitoring systems with intelligent, predictive technology that addresses ESG pressures and rising energy waste.

What it does

SusTainLabs is an end-to-end AI-powered energy intelligence platform that goes beyond simple monitoring to actively manage telecom infrastructure. Its core capabilities include: • Real-time Optimization: It balances power loads between the grid and renewable energy sources to minimize costs. • AI-Driven Predictions: The system forecasts energy demand and detects anomalies 48-72 hours in advance to prevent waste. • Autonomous Inspection: It deploys drones for remote diagnostics and tower inspections, reducing the need for manual field visits.

How we built it

We constructed a comprehensive solution leveraging Edge AI to ensure low latency and high security: • Hardware: We utilized AMD Ryzen Embedded processors to deliver 39 TOPS of AI performance locally, ensuring 24/7 operation with minimal power consumption. • AI & Computing: The AMD ROCm platform facilitates our AI acceleration, while AMD Instinct accelerators supported our high-performance training requirements. • Software Stack: The application is built using Python, TensorFlow, and PyTorch for AI models, with a frontend/backend powered by Next.js, Node.js, and TailwindCSS. • Data Infrastructure: We implemented MQTT and Kafka for real-time data streaming and integration.

Challenges we ran into

A major challenge in this domain is the limitation of traditional Energy Management Systems (EMS), which are reactive and lack predictive intelligence. Furthermore, relying solely on cloud-based analytics introduces critical latency issues, data privacy risks, and high ongoing costs. We had to engineer a solution that moved processing to the "edge" (directly on the tower sites) to ensure real-time analytics without the lag or security exposure associated with the cloud.

Accomplishments that we're proud of

We have projected significant real-world impacts for our solution: • 25-35% Energy Reduction: Achieving massive savings per tower through intelligent load balancing. • 40% Carbon Emissions Cut: Equivalent to planting 500 trees per site annually. • 95% Forecast Accuracy: Enabling proactive management rather than reactive firefighting. • 60% Faster Maintenance: Drastically reducing downtime through predictive alerts.

What we learned

We learned that Edge Computing is superior to Cloud Computing for remote telecom operations. By processing data on-device with AMD architecture, we achieved 10x faster inference compared to cloud alternatives and eliminated latency completely. We also discovered that local processing is essential for meeting strict telecom security requirements and regulatory compliance regarding data privacy.

What's next for SustainLabs

We are targeting a ₹40,000 Crore addressable market in India's telecom energy sector. Our immediate next steps involve deploying our SaaS and hardware bundles to Tier-1 operators to capture an initial 1% market share, which represents ₹400 Crore in annual revenue. We aim to scale our solution to support the massive energy demands of the continuing 5G rollout

Built With

• amazon-web-services
• apache-kafka
• azure
• built-with-python
• google
• mongodb
• mqtt
• next.js
• node.js
• postgresql
• pytorch
• react
• tailwindcss
• tensorflow