We are developing OPTeam, a web app based on a digital twin, based upon the fire service graph, enabling the study, exploration, and simulation of operational issues in a controlled environment. We are also developing OPS Ready (sold as a white label product to the French Ministry of the Interior under the name NexSIS), a mobile and sovereign ecosystem including several smartphone applications and an administration web app for supervising firefighters' operational activities, mobilizing personnel, and managing firefighters' availability in real time. We have implemented biomathematical algorithms based upon chronobiology science, making in both cases the comand and control and the chain of command able to estimate the teams and individuals fatigue, fatigue due to an increasing number of interventions (population's aging issues) and also their increasing duration (events related to climate change, wildifres, floods...).If the two solutions are TRL9, our evidence based and science based features and biomathematical algorithms are TRL 6, tested and validated in ultra trail, sailing and ultra cycling competition, and to be industrialized in our two apps next year. Opteam will be the first application to benefit from the evolution of our algorithms.
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OPTeam is a web application based upon explainable AI, designed for fire and rescue services, and more broadly, for organizations whose missions aim to cover or protect a territory as quickly as possible with optimized and interdependent resources. Our ambition is to make it easy to understand the fundamental issues affecting the optimization of fire and rescue services.Most of the time, these issues are closely linked to the allocation and planning of resources across the territory, problems related to some of the most difficult mathematical problems to solve (combinatorial analysis), based on factorial functions, mathematical functions whose complexity grows most rapidly... Opteam makes some solutions to these problems within reach of operational staff and their decision-makers, by making them understandable and explainable, allowing them to objectively verify their hypotheses based on field experience.
Thanks to our expertise in complex systems analysis, combinatorial optimization, chronobiology and our dedicated scalable computing power, it is possible to simulate over 100,000 operations and all other related parameters, dashboards and variables in just a few minutes during a single simulation. This makes it easier for you to multiply hypotheses and strategies about demand rates & ops related fatigue, taking into account the whole rescue service (i.e. 110 fire stations interacting at the same time and sharing the same budget to defend a whole territory, the entire roster of the fire service, and the engines availability), each time with a clearly displayed confidence score and limits... You decide; OPTeam's explainable AI extends your arm and does not replace your brain. The whole technology is AI Act compliant, and made with 100% sovereign tech, avoiding foreign interferences on critical issues...
Using a digital twin approach based upon complex systems analysis, the tool allows users to EXPLORE historical data through a series of dashboards on one hand, as well as SIMULATE scenarios and analyze their impacts i.e. on response time, ops demands, fatigue of teams and individuals on the other hand. OPTeam aims to allows users to increase their understanding and control over operational analysis and risk mitigation strategies at a whole territory /network level. It may also serves as a training aid for officers and decision makers, helping on experience feedback and analysis, and a tool for building data driven business continuity plans. OPTeam can already be used to simulate numerous scenarios. For example, it can simulate a change in the number of firefighters or vehicles available at an existing firestation over a specific period—a typical use case being the simulation of a fire station closure. It can also simulate changes to operating rules, such as readiness rules, defense/ subbrogation lists, vehicle equivalencies, etc.
A friendly tech-commando aiming to balance a hands on experience learned the hard way as first responders, volunteer firefighters, police & military officers, and an international academic level and deeptech developpement proficiency (Multiple PhDs, MEng from ENS Lyon, MIT, Paris Dauphine, EFREI, ENSIMAG, ENSEIRB, ENSAM, INRIA, Centrale Supelec), at ease with complex systems network and graph analysis, combinatorial optimization, time series, devops, open source and sovereign tech (0%.GAFAM)
A friendly tech-commando aiming to balance a hands on experience learned the hard way as first responders, volunteer firefighters, police & military officers, and an international academic level and deeptech developpement proficiency (Multiple PhDs, MEng from ENS Lyon, MIT, Paris Dauphine, EFREI, ENSIMAG, ENSEIRB, ENSAM, INRIA, Centrale Supelec), at ease with complex systems network and graph analysis, combinatorial optimization, time series, devops, open source and sovereign tech (0%.GAFAM)