A New Paradigm in Fire Safety with Digital Twins and Artificial Intelligence
Detectium revolutionizes anomaly detection and fire prevention for industrial facilities by integrating electro-optical/thermal (EO/IR) sensors technology with digital twinning and machine learning algorithms.
The Solution
Our clients in the industrial and agricultural sectors benefit from our solution, utilizing it to proactively prevent fires while enabling the following features before, during, and after an incident:
Before incidents
- Anomaly detection to prevent fire
- Security integration allowing to evaluate real-time occupancy level
- Fire propagation scenario modelling and simulation
During incident
- Early fire detection
- Accurate fire localization
- Real time data feed available for civil defence responders “God’s eye view”
- Real-time escape route selection (based on evolving threat” for every floor.
After incidents
- Root cause identification
- Damage assessment
- Insurance claim verification
Our clients in the industrial and agricultural sectors benefit from our solution, utilizing it to proactively prevent fires while enabling game-changing features before, during, and after an incident.
For our non-industrial customers, we offer a simplified version of our solution that harnesses the capabilities of computer vision. This streamlined offering provides an accessible and user-friendly experience, catering to a wide range of customers with diverse needs. By leveraging computer vision technology, our simplified solution still delivers effective fire detection and safety features, tailored to non-industrial settings.
Product and Service Offerings
Industrial Uses
A digital twin is a real-time virtual representation of physical objects. Our solution comprises hardware and software components, cloud services, and machine learning (ML) technology, integrating Infrared and RGB sensors, 3D model visualization, and data analytics to elevate fire safety standards.
Our highly sensitive thermal and RGB sensors can detect even small flames indoors and outdoors. The operation of our flame detector is inherently much faster than that of conventional fire detectors based on smoke or heat detection.
We provide a flexible 3D visualization service tailored to the complexity and size of each site, catering to the diverse needs of our industrial customers. Our service can be utilized for a range of applications, including workflow simulation and optimization, as well as indoor navigation. With our advanced 3D visualization technology, industrial clients gain valuable insights into their sites, enabling them to optimize processes, streamline workflows, and enhance overall efficiency.
Leveraging historical data and predictive analysis, we offer comprehensive data analysis and machine learning solutions to foresee fire hazard risks at your facility. With our subscription-based computer vision service, you gain access to an ever-improving fire detection system that harnesses the power of advanced algorithms and cutting-edge technology. By subscribing to our service, you can stay ahead of potential fire hazards, proactively mitigate risks, and ensure the safety and security of your premises.
The Advantages of Detectium's Solution
Speed
Our solution incorporates a state-of-the-art highly sensitive IR detector, enabling the detection of small temperature anomalies and flames both indoors and outdoors. In addition, we enhance the system with active learning on an RGB sensor, significantly elevating visibility and accuracy levels. With a rapid detection time of under 9 seconds for small fires, we outperform current fire detection systems, ensuring quick and efficient fire detection.
Accuracy
Our cutting-edge thermal and RGB camera sensor technologies offers an expansive detection range, setting a new standard in fire detection capabilities. Our solution stands out by detecting flames of 0.01 square meters size from an impressive distance of 60 meters away. In comparison, traditional fire detection methods using smoke detectors typically have a limited range of approximately 10.5 meters, and heat detectors come in at around 7.5 meters.
Use of data
By harnessing the power of machine learning algorithms to analyze historical data collected at the factory over an extended period, specifically focusing on various fire hazard incidents our solution intelligently identifies and maps high-risk areas, enabling more effective and targeted risk mitigation strategies for the future. Additionally, we continuously retrain our machine learning model to ensure its adaptability and efficiency in managing all possible scenarios.
The Benefits of Digital Twin for Safety
Team
Siavash Khajavi
Siavash, the CEO and co-founder of Detectium holds a PhD and has conducted extensive research on digital twins. His vision is creating a world where the digital representation of all objects can be efficiently and accurately created to enhance the safety in the physical world.
Adriaan Knapen
Adriaan is a CINO at Detectium. His wide range of expertise includes embedded software development, release and test automation, cloud infrastructure, and software development culture.
Zixuan Liu
Zixuan is the CTO and a computer vision and embedded system expert at Detectium, enabling seamless integration of image data and AI models. She has deep knowledge of AI research and state-of-the art AI models.
Aarni Huuskonen
Aarni is the CFO and key account manager at Detectium. Having experience from Nordea and as a business analyst in a scaleup, he ensures Detectium’s path to fast and profitable growth.
Mehdi Moshtaghi
Mehdi is a machine learning export at Detectium. He has hands-on experience in MLOps.
Advisors
Pasi Korhonen
Pasi is currently the Chief Specialist of business development and innovation with LähiTapiola Insurance Company. He is Detectium’s industrial advisor who assists the company in driving growth and fostering innovation.
Jan Holmström
Professor Jan Holmström is currently a Professor of operations management with Aalto University, Finland. He is also an expert in supply chain management and design science research. With an extensive publication record, he is Detectium’s distinguished academic advisor.
Kary Främling
Professor Kary Främling has extensive knowledge from Umeå and Aalto University in building information management and digital twinning technologies.
Company Background
Established in 2021, Detectium is a startup in Finland. The project results from a collaboration between three partners: EIT Digital, Business Finland and Aalto University, to reduce casualties from industrial fires by digital twinning technology and AI.
Detectium has received funding from the EIT Digital Open Innovation Factory 2023 program as an innovation activity in the area of the digital industry. Detectium has also received funding from Business Finland in 2023 for research and development of the solution.
Digital twin definition and background:
A digital twin is the digital counterpart of a physical asset that specifically works with real-time data fed by sensor systems to record and analyze the real-time structural and environmental parameters of a physical asset. This is done for the purpose of performing highly accurate simulations and data analytics.
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