Description

1. Title AI4Fire 2. Description The value proposition is based on create a fast, continuous and cheap protection system fighting against one of the four axes of the fire tetrahedron, “the fuel”, in this case “the fuel are textiles”. To fight against fire, it is necessary to stop one of the four tetrahedron axes to break the chain reaction. Basically, in order to control the fuel, for SMEs must be analyzed the quantity of Raw Material, Inventory & Finished Goods, the distance from source of ignition and housekeeping The product is a System based on a Mathematical Artificial Intelligence for Fire AI4Fire, which continuously evaluates, analyzes the and generates warnings about the housekeeping conditions, quantity of raw material, inventory & finished goods and proximity of ignition sources, with the use of sensorics. The Capacitive proximity sensors and Proximity sensors will be required to operate under a platform of Programmable logic controllers (PLC) generating all the essential information for the system. This system will also provide a large amount of data about the way of good industry practices are used in the SMEs and the relation between claims or relevant emerging SMEs. 3. A detailed description of the device and it's functionalities/properties. a. Protection Effectiveness (how effectively does the device fight against fire) The classification based on NFPA establishes that textiles are categorized in a type of risk Extra Hazard Group I with a SIC CODE 2299 for Textile Goods, NEC. The classification of the degree of risk, is classified as high, therefore, it is understood that the SMEs companies involved in the work and operations with textiles can achieve a total loss of 100%. The value proposition is based on create a fast, continuous and cheap protection system fighting against one of the four axes of the fire tetrahedron, “the fuel”, in this case “the fuel are textiles”. To fight against fire, it is necessary to stop one of the four tetrahedron to break the chain reaction. Basically, in order to control the fuel, must be analyzed the quantity, distance from source of ignition, like electrical devices, lighting and household heating systems, such as boilers. It´s also important to take control of housekeeping quality of Raw Material, Inventory & Finished Goods. Obviously, the variables are too numerous to analyze only one of the tetrahedron axes. But a mathematical system based on sensorics and artificial intelligence can make easy decisions for managers in SMEs without been a fire expert and provide continuous reports about the behavior of warehouses and production. With this system the manager only cares about the core business and not be involved about fire specialization. The product is a System based on a Mathematical Artificial Intelligence for Fire AI4Fire, which continuously evaluates with statistics and mathematical decision making and generates warnings about the housekeeping conditions, quantity of raw material, inventory & finished goods and proximity of ignition sources, with the use of sensorics. The Capacitive proximity sensors and Proximity sensors operating under a platform of Programmable logic controllers (PLC) generate all the information required by the system. This system works with prevention and education to the people involved in textile SMEs, the system will also provide a large amount of data about the way of good industry practices are used in the SMEs and the relation between claims or relevant emerging SMEs. b. Fast Response (detection & reaction) The response is based on immediately action. For example, normally the people involved in a warehouse or production operation need to broke some rules, like the housekeeping rules just for a while and going back immediately to the path. The problem is when the broken rule is not solved, leaving raw material in the evacuation route, in this case, if the problem it´s not corrected people and materials will be exposed if a fire begins. Continuously the sensors will detect when a path is blocked more than 10 minutes or when raw materials overpassed the natural capacity of the warehouse exposing the SMEs to an imminent fire expansion. A supervisor will receive a warning alert and the orders of actions to be taken when these raw materials are leaved in an unauthorized place. c. Cost Efficiency The cost efficiency can be developed with strategical structure of: - Key partners the enterprises that develop sensorics and PLCs (can be used pneumatics energy from the production), team of handworkers, team of fire engineers to optimize installation sensors and to improve the system requierements - Key Resources, System Platform. Technology infrastructure - Key Activities, Platform Development, Data Center operations Management, The system will continuously analyses the next variables: - Analysis of maximal capacity of Warehouses - Analysis of Probability of Fire - Analysis of Risk Scenario - Analysis of human behavior - Analysis of Loss Prevention variables d. Installation Effort (retrofitting on existing infrastructures) System Platform, will require local computers. PLCs and Sensorics, will require electropneumatic energy, sensors, PLCs and handworkers Other devices like heat and smoke sensors are compatible. e. Maintenance Effort The system must be actualized frequently with the different kind of textiles, because not all textiles have the same burn capacity and toxicity characteristics. Also, the sensors must have intrinsic security against fire and IP NEMA protection over 66 to guarantee that those sensors are not going to be the source of ignition. f. A friendly user The system platform can be developed under Android and IOs platforms to be friendly about communications to the supervisors and workers. A robust and more detailed system can be used for Business Intelligence, Engineering & Project departments. g. Scalability (bigger companies & other industries) The scalability of these protection system can be easily being installed in other SMEs and also in other industries. It’s going to be important to classify under Sic Code and NFPA in order to invest more or less to obtain the answer of variables. The Scalability of the system can receive other quality and quantity of sensors, like optic sensors, thermographic cameras, hygrometric sensors and others which can be supported by robust enterprises

References

FIRE AWARENESS IN TEXTILE INDUSTRY SMEs. (1st July de 2018). Market Research. Hurley, M. J. (2015). SFPE Handbook of Fire Protection engineering. New York Heidelberg Dordrecht London: Springer. Labor, U. D. (1996). OSHA Handbook for Small Businesses. Washington, DC: Safety Management Series OSHA 2209 Revised. National Fire Protection Association. (2009). Manual de Protección contra incendios. Quincy, Massachussetts.

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