Founder of ThermoAI, contributor to VentureBeat's AI, Industrial AI expert
ThermoAI
The startup employs artificial intelligence to optimize combustion processes in industrial applications, enhancing fuel efficiency and minimizing emissions. This technology directly targets the significant environmental impact of industrial combustion, contributing to a reduction in global greenhouse gas emissions.
- Artificial Intelligence
- Data & Analytics
- Clean Technology
- Industrial Automation
- Software Only
Updated 23 months ago
Funding
Raised to date
$452.8KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Industrial combustion processes contribute significantly to greenhouse gas emissions and often operate at suboptimal fuel efficiency due to the complex interplay of various factors. Traditional methods of optimizing these processes are reactive and unable to adapt to real-time changes in operating conditions and fuel composition.
Solution
ThermoAI provides an AI-powered solution that optimizes combustion processes in real time for industrial and defense applications. By leveraging operational data from combustion facilities, the AI proactively adjusts input settings to maximize combustion efficiency and minimize emissions. The system uses cyber-physical systems (CPS) and clustering machine learning to crosscheck signals in Internet of Things (IoT) systems, increasing accuracy and trust. Additionally, ThermoAI offers FuelSim, which employs AI and digital twin technology to simulate the performance of different jet fuels, detect contamination, and reduce fuel waste.
Target Audience
ThermoAI targets defense and industrial clients seeking to improve operational efficiency, reduce emissions, and optimize fuel consumption in combustion processes.
Features
- Real-time optimization of combustion processes using AI trained on operational data
- Cyber-physical systems (CPS) and clustering machine learning for crosschecking IoT signals
- FuelSim digital twin technology for simulating jet fuel performance and detecting contamination
- Proactive adjustment of input settings to maximize combustion efficiency
- Reduction of greenhouse gas emissions through optimized combustion
- Detection of contaminated fuel and decreased fuel waste