ARYABHAT-1: India’s First Fully Analog AI Processor

Designed & Built in India — A Fully Analog, Energy-Efficient, Performance-Scalable AI Processor

Key Features:

• 8-Core Fully Analog Architecture
• Technology & Energy Scalable Design
• Custom Compiler for AI/ML Algorithms
• Python-based Automated Testing Framework

Built from transistor to system level, ARYABHAT-1 allows users to configure energy and performance modes — making it ideal for edge AI tasks requiring ultra-low power.

---

Bird Hotspots: Low-Power Acoustic Classification for Ecological Monitoring

Identifying Bird Habitats using TinyML & Neuromorphic Audio Processing

This project from the NeuRonICS Lab, IISc, presents a novel low-power acoustic classification system to automatically identify bird hotspots — enabling real-time ecological insights using resource-constrained, battery-powered devices.

Key Features:

• TinyML-powered low-power acoustic classification
• Neuromorphic audio front-end using in-filter computation
• Template-based SVM model requiring less data and robust to noise
• Easy deployment on low-power microcontrollers

Hardware Highlights:

• TI CC1352 Launchpad (ARM Cortex M4F)
• MEMS microphone for audio capture
• Real-time audio buffering and classification
• On-device bird detection logs

This system enables scalable, automated monitoring of bird species without human intervention — crucial for biodiversity conservation and habitat mapping.

---

mmWave Radar for Activity Recognition and Localization

Real-time Multi-person Tracking for Healthcare and Surveillance

This project from the NeuRonICS Lab at IISc leverages mmWave radar to track and classify human activities in real-time, with a focus on healthcare, psychiatric ward, and custodial monitoring applications — all while preserving privacy.

Key Features:

• Radar-based Localization & Activity Recognition
• Simultaneous Multi-person Tracking
• Three-layer CNN for Real-time Classification
• Python-based GUI for Visualization & Logging

Technology Highlights:

• Uses IWR6843 mmWave radar (60–64 GHz)
• Robust in low light, dark, or foggy environments
• Preserves privacy by avoiding image capture — uses point cloud data
• Tracks range, velocity, acceleration & zone-based localization
• Supports classification: walking, sitting, resting, jumping, etc.

Unlike cameras, this contactless solution ensures privacy and works reliably in challenging environments. It’s a powerful tool for non-intrusive monitoring of patients or inmates, offering compact, low-power, and real-time insights.

---