AEInnova develops self-powered, batteryless sensors that convert residual heat into energy for real-time monitoring of industrial machinery, enabling predictive maintenance without downtime. Their technology enhances operational efficiency by detecting potential failures in rotating equipment, reducing maintenance costs and minimizing unexpected production halts.
Funding
Funding not disclosed
Founders
Product
Problem
Many industrial facilities rely on battery-powered sensors for machine monitoring, leading to high maintenance costs associated with battery replacements and disposal. Traditional monitoring systems also require complex installations, often necessitating production downtime.
Solution
AEInnova provides self-powered, wireless sensors that harvest energy from residual heat, enabling continuous monitoring of industrial equipment without batteries. These sensors detect temperature and vibration, allowing for predictive maintenance and early detection of potential failures in rotating machinery. The system includes the InduEye sensor family and the DAEVIS cloud platform for data visualization and analysis. By eliminating the need for batteries and offering non-invasive installation, AEInnova's solutions reduce maintenance costs, minimize downtime, and improve operational efficiency.
Target Audience
The primary customers are industrial facilities in sectors such as oil & gas, manufacturing, chemical, and energy, seeking to optimize maintenance schedules, reduce operational costs, and improve equipment reliability.
Features
- Self-powered sensors that convert residual heat into electricity, eliminating the need for batteries
- Wireless communication using Lora technology for long-range data transmission
- Tri-axial vibration monitoring to detect imbalances, misalignments, and bearing defects
- Temperature measurement for thermal profiling and overheating detection
- ATEX/IECEX certified sensors for use in hazardous environments
- DAEVIS cloud platform for real-time data visualization, historical trending, and predictive analytics
- Non-invasive installation that does not require production downtime
- Integration with third-party sensors and monitoring systems