Description:FIELD OF THE INVENTION
The present invention broadly relates to AI-Driven Hybrid Fire Suppression and Risk Assessment System. This multi-functional fire suppression system introduces ground-breaking innovations that enhance safety, efficiency, and environmental compliance. To overcome these limitations, this invention integrates multiple advanced fire detection and suppression technologies to enhance efficiency, responsiveness, and safety

BACKGROUND OF THE INVENTION

Fire safety remains a critical challenge, with conventional fire detection and suppression systems primarily relying on smoke and heat sensors. Traditional fire safety solutions, including standalone fire alarms, sprinkler-based suppression mechanisms, and manual firefighting interventions, have inherent limitations. These systems are reactive rather than proactive, leading to delays in fire suppression and increasing risks to life and property. Advancements in Artificial Intelligence (AI), the Internet of Things (IoT), blockchain, drones, and Augmented Reality (AR) present new opportunities for enhancing fire risk assessment, detection, and suppression. However, existing solutions lack an integrated approach that predicts fire hazards before they occur, optimizes suppression techniques, and provides real-time guidance to affected individuals and emergency responders. Additionally, current fire safety technologies do not incorporate self-learning AI models, biometric-based personalized alerts, gamified fire safety training, or AI-assisted firefighting tools. Most conventional fire response systems also fail to utilize solar-powered, sustainable energy solutions or voice-activated commands for hands-free operation.
Fire suppression technologies have evolved significantly to meet the demand for faster, more efficient, and environmentally safe fire extinguishing solutions. However, conventional methods present several challenges:
Halon-Based Extinguishers: Highly effective in fire suppression but harmful to the ozone layer, leading to global regulatory bans (e.g., Montreal Protocol, 1987).
Gas-Based Suppression Systems (CO₂, IG541, Nitrogen, Argon, etc.): Reduce oxygen concentration to extinguish fires but pose suffocation risks in confined spaces. Require high-pressure storage, increasing explosion hazards and necessitating robust safety measures.
Powder-Based Extinguishers: Leave behind residue contamination, making them unsuitable for sensitive environments such as data centers, laboratories, and precision manufacturing units.
Water and Foam-Based Systems: Require extensive piping infrastructure and high-pressure storage, leading to high installation and maintenance costs. Ineffective against electrical and oil-based fires, limiting their industrial applicability.
Aerosol Fire Suppression Systems: Perform well in enclosed spaces but suffer from reduced efficiency due to cooling filtration layers that weaken suppression effectiveness.
Cold-Weather Incompatibility: Many liquid-based fire suppression systems fail in sub-zero temperatures due to increased viscosity, reducing deployment feasibility in cold climates.
Additional Challenges of Traditional Fire Safety Solutions:
• Delayed Detection: Conventional heat and smoke sensors activate only after a fire has developed significantly, reducing response time.
• High False Alarm Rate: Sensors often misinterpret environmental factors like steam or dust as fire, leading to unnecessary evacuations and disruptions.
• Limited Scalability: Physical sensors require dense deployment to ensure effective coverage, making large-scale implementation impractical in forests, warehouses, and industrial plants.
• Maintenance Issues: Fire detection tubes made from polyamide resin are prone to gas leakage over time, reducing reliability and increasing operational risks.

SUMMARY OF INVENTION
This invention integrates multiple advanced fire detection and suppression technologies to enhance efficiency, responsiveness, and safety. It utilizes AI-based image recognition with computer vision and deep learning algorithms to detect early fire signs before visible smoke or heat buildup, ensuring faster response times. Multi-layer smoke sensors are designed for deployment in high-ceiling areas, improving detection accuracy in large industrial spaces. EVOH-based fire detection tubes employ advanced gas barrier technology to prevent leakage and ensure consistent fire suppression in hazardous environments. Autonomous fire extinguishing systems operate independently of electricity, ensuring functionality even during power failures. They incorporate a pressure-free, self-activating suppression mechanism that eliminates the need for manual activation, external power, or high-pressure storage. Nano-technology-based ultra-fine extinguishing powder provides seven times higher efficiency than standard ABC-class extinguishing powders. The system is designed to activate automatically at 170°C, ensuring immediate response without human intervention. The extinguishing agent is released through a thermally activated signal cord, which reacts to heat or open flames, breaking the containment membrane and dispersing the powder over the fire. The system is eco-friendly and composed of non-toxic, sulfate-free, and barium-free materials to minimize environmental impact. Its modular and compact design allows scalable deployment, enabling multiple units to be linked for broader fire coverage. Unlike conventional pressurized extinguishers, this system is maintenance-free, reducing long-term costs and enhancing safety by eliminating risks associated with high-pressure storage. AI-driven fire risk prediction and emergency response capabilities further enhance the system’s efficiency. Predictive fire analytics use AI algorithms to analyze environmental data such as temperature, humidity, and gas emissions to predict potential fire hazards before ignition. Real-time emergency guidance provides biometric-based personalized alerts and voice-assisted evacuation instructions to affected individuals. AI-assisted firefighting tools integrate with drone-based fire suppression units and AR-guided emergency response systems for enhanced fire control.

DETAILED DESCRIPTION OF THE INVENTION

This multi-functional fire suppression system introduces groundbreaking innovations that enhance safety, efficiency, and environmental compliance. It eliminates the need for high-pressure storage, allowing for safer handling and easier deployment compared to traditional gas-based suppression systems. The system employs a hybrid fire suppression approach, utilizing a combination of chemical aerosol, foam, mist, and liquid agents to provide superior fire suppression across various scenarios. It enhances safety in enclosed spaces by effectively suppressing fires without depleting oxygen, ensuring the well-being of occupants. Additionally, it prevents re-ignition by forming a protective anti-flame layer that minimizes the chances of fire resurgence. Designed to meet global safety standards, the system is free from ozone-depleting substances and toxic byproducts, ensuring full environmental compliance. It also remains fully functional in sub-zero temperatures without viscosity-related issues, making it highly reliable in cold-weather conditions.
The advanced fire detection and suppression system integrates AI-driven YOLOv3-CA fire recognition, utilizing an SE residual module and spatial feature fusion for real-time image-based fire detection. Multi-layer smoke detection is achieved through strategically placed sensors that enable early fire detection before smoke reaches the ceiling. EVOH-based fire detection tubes detect and suppress fires at temperatures as low as 92°C, offering superior performance compared to traditional polyamide-based tubes. The autonomous suppression system operates without electrical power, making it ideal for hazardous and power-sensitive environments.
This invention offers substantial advantages over traditional fire suppression systems. It provides a non-toxic, ozone-safe alternative to halon-based systems. Unlike CO₂ and inert gas systems, it extinguishes fires without reducing oxygen levels, making it safer for enclosed spaces. Compared to powder-based extinguishers, it leaves no solid residue, ensuring a clean suppression process. It effectively handles Class A, B, C, and electrical fires without causing short circuits or water damage, surpassing the limitations of water and foam-based systems. Traditional aerosols are improved with enhanced suppression efficiency by eliminating cooling filtration layers. The system functions reliably in extreme temperatures below -50°C, ensuring optimal cold-weather performance. Additionally, it reduces reliance on ceiling-mounted smoke detectors, minimizing maintenance issues related to gas leakage in fire detection tubes, improving overall reliability and efficiency.
The novel advancement of this invention is achieved through several key inventive steps. Unlike traditional fire suppression systems that rely solely on reactive mechanisms, this innovation integrates AI and IoT to enhance proactive fire prevention and suppression. Predictive AI analytics, real-time monitoring, and IoT connectivity enable early detection and rapid response, significantly improving fire safety. Automation is further enhanced through the deployment of autonomous drones, vehicles, and exoskeletons that can independently navigate, assess, and respond to fire incidents, increasing both efficiency and safety. Unlike conventional systems that rely on a single suppression method, this system employs a multi-layered approach by combining foam, mist, gas, and nano-powders, ensuring superior fire suppression across all fire classes, including A, B, C, D, F, and K.
To ensure broad and exclusive patent rights, this invention emphasizes several unique innovations. AI and quantum computing-based fire prediction models enable ultra-fast fire risk assessment by simultaneously processing multiple risk factors, allowing for proactive fire prevention strategies. AI-powered biometric fire safety assistance customizes fire alarms and evacuation instructions based on an individual's medical conditions, mobility constraints, and real-time location. Blockchain-based fire data protection secures fire incident logs, prevents fraudulent claims, and ensures transparency in post-incident investigations. A multi-mode smart fire suppression system utilizes AI-controlled dispersion of aerosols, foam, water mist, and inert gas to target different fire classes with maximum efficiency. Self-deploying smart drones and firefighting exoskeletons integrate AI-powered autonomous drones for aerial fire suppression and robotic exoskeletons that enhance firefighter endurance and safety. AI-integrated building fire safety management continuously monitors building infrastructure, detects weak structural points, and suggests preemptive measures to reduce fire risks before ignition occurs. High-altitude fire suppression deployment features autonomous drones equipped with precision AI algorithms for targeted suppressant release over large-scale wildfire areas. Real-time AI-based fire spread analysis continuously monitors fire movement and predicts its spread, providing real-time insights for better resource allocation and evacuation strategies. A smart traffic and emergency routing system integrates AI with city traffic control to adjust signals and reroute vehicles, ensuring fast and unobstructed access for emergency responders. AI-optimized water conservation in fire suppression regulates water mist and foam usage, reducing excess water damage while improving suppression efficiency. Next-generation thermal imaging for firefighter navigation employs AI-enhanced thermal sensors to provide real-time heat mapping, allowing firefighters to navigate through dense smoke and hazardous environments. AI-powered hazardous material detection uses smart sensors to identify flammable and toxic substances in industrial settings, issuing early warnings to prevent catastrophic fires. Fire safety gamification and AR-based training leverage AI-powered virtual reality and augmented reality modules for interactive public and professional fire safety education. Autonomous underground and tunnel fire suppression deploys smart robotic systems to navigate underground tunnels and enclosed spaces, suppressing fires in hard-to-reach areas. AI-powered smoke and gas differentiation sensors intelligently distinguish between harmless fumes and dangerous fire smoke, significantly reducing false alarms. Dynamic fireproofing solutions feature AI-controlled self-activating fireproof coatings and materials that deploy a protective shield when heat levels surpass a predefined threshold. Next-generation AI fire emergency coordination integrates a fully AI-based system to manage communications between fire departments, hospitals, and disaster response units, ensuring seamless coordination during emergencies. , Claims:We Claim:
1. An advanced fire detection and suppression system, comprising:
an AI-driven fire recognition module utilizing deep learning and computer vision to detect early fire indicators;
a multi-layer smoke detection system with strategically positioned sensors for early fire identification;
an EVOH-based fire detection tube designed for rapid response at temperatures as low as 92°C;
an autonomous fire suppression mechanism that operates independently of an external power source;
a hybrid suppression system deploying a combination of aerosols, foam, mist, and inert gases to extinguish fires across multiple classes (A, B, C, D, F, and K);
a self-deploying firefighting drone integrated with AI algorithms for aerial fire suppression;
a biometric-based fire safety assistance system that customizes evacuation guidance based on individual health conditions and real-time location; and
a blockchain-enabled incident logging system that ensures secure, tamper-proof records of fire incidents and suppression activities.

2. The system of claim 1, wherein the AI-driven fire recognition module employs a YOLOv3-CA neural network with an SE residual module for improved real-time fire detection accuracy.

3. The system of claim 1, wherein the multi-layer smoke detection system includes gas differentiation sensors that distinguish between harmless fumes and dangerous fire smoke to reduce false alarms.

4. The system of claim 1, wherein the EVOH-based fire detection tube activates at a pre-determined temperature threshold and releases an ultra-fine nano-powder extinguishing agent with a suppression efficiency seven times greater than conventional ABC-class extinguishing powders.

5. The system of claim 1, wherein the autonomous fire suppression mechanism is activated by a thermally sensitive signal cord that breaks containment and disperses the extinguishing agent upon exposure to fire.

6. The system of claim 1, wherein the hybrid suppression system dynamically adjusts the suppression method based on real-time fire classification using AI-based fire spread analysis.

7. The system of claim 1, wherein the self-deploying firefighting drone is equipped with AI-powered navigation, thermal imaging, and precision suppressant release for high-altitude fire suppression in wildfire scenarios.

8. The system of claim 1, wherein the biometric-based fire safety assistance system integrates with smart wearables to provide real-time alerts and emergency assistance based on an individual's physiological condition.

9. The system of claim 1, wherein the blockchain-enabled incident logging system maintains immutable records of fire events, suppression activities, and environmental conditions for post-incident analysis and compliance verification.
10. The system of claim 1, further comprising an AI-integrated building fire safety management system that monitors structural integrity and environmental conditions to predict fire risks and suggest preemptive safety measures.