Advanced Battery Health Monitoring

AI-powered condition monitoring that predicts battery failures before they occur. Maximize uptime and reduce replacement costs.

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Voltage Monitoring

Thermal Analysis

SoC Estimation

Safety Monitoring

42%
Reduction in Downtime
35%
Lower Replacement Costs
94%
Detection Accuracy
5M+
Data Points/Day

Business Context & Market Potential

Our solution addresses critical challenges in battery management across multiple industries, delivering measurable ROI through advanced IoT and AI technologies.

Application Areas

Electric vehicles, telecom towers, renewable energy storage, data centers, UPS systems, and industrial automation.

Problems

Unexpected battery failures, safety risks from thermal runaway, high replacement costs, and lack of real-time monitoring.

Traditional Solutions

Manual inspections, non-networked BMS logs, and reactive maintenance approaches.

Need for Novel System

Affordable, continuous monitoring with real-time AI alerts and predictive maintenance for battery systems.

Our Solution

Edge system with ARM SOC Based AI controllers for electrical/thermal monitoring and cloud-based AI analysis.

Unique Selling Proposition

Plug-and-play retrofit compatibility with predictive scoring and digital twin visualization.

Benefits

Detects issues before failure, reduces costs by 20-30%, extends battery lifespan, and improves safety.

Target Customers

EV fleet operators, telecom infrastructure providers, data centers, and battery OEMs.

Customer Impact

Enhanced uptime and reliability, streamlined maintenance, and data-driven decision-making.

Business Potential

  • India: ~20 million deployed batteries across industries
  • Global: $12B+ opportunity in battery analytics by 2030

Key Features

Comprehensive monitoring capabilities powered by IoT and AI to transform your battery management strategy.

Voltage Monitoring

Voltage Monitoring

Real-time monitoring of cell and pack voltages with AI anomaly detection.

Thermal Analysis

Thermal Analysis

Continuous temperature monitoring to prevent thermal runaway risks.

AI Analytics

AI-Powered Analytics

Advanced machine learning models to predict failures and recommend actions.

Digital Twin

Digital Twin Visualization

Virtual representation of battery packs with real-time health status.

SoC Estimation

SoC Estimation

Advanced algorithms for accurate state of charge calculation.

Mobile Access

Safety Monitoring

Early detection of potential fire risks and safety hazards.

Battery Status Visualization
Healthy Warning Critical
3.65V
25°C
3.64V
26°C
3.66V
24°C
3.63V
27°C
3.61V
29°C

Frequently Asked Questions

Get answers to common questions about our platform.

Our AI-powered analytics achieve 94% accuracy in predicting battery failures, with false positive rates below 4%. Accuracy improves as the system learns your specific battery characteristics.

Yes! Our solution is designed as a retrofit kit that can be installed on existing battery systems without modifications. Most installations take less than 1 hour per battery pack.

We support Wi-Fi, Ethernet, 4G/LTE, and LoRaWAN connectivity options. The system can store data locally during connectivity outages and sync when connection is restored.

Our system typically detects developing issues 7-30 days before failure occurs, giving you ample time to schedule maintenance and prevent unplanned downtime.

Get Started Today

Ready to transform your battery management? Contact our team for a personalized consultation.

Why Choose Battery Health AI?

  • Proven Technology: Deployed across 50+ installations
  • Industry Expertise: 8+ years in battery monitoring
  • Custom Solutions: Tailored to your specific requirements
  • 24/7 Support: Dedicated technical assistance
  • ROI Focused: Clear path to cost savings and efficiency
Contact Information

research@intuitiverobotics.in

+91 9433043040

565, Central Road
Sonarpur, WB 700150