Autonomous Intelligent System for Rapid Wildfire Detection, Eradication, and Prevention

A system for rapid ember eradication to prevent wildfire ignition, comprising:

• (bb) a plurality of AI Sensor Network Modules (AISNM) and Fire/Ember Extinguishing Modules (FEM), distributed across wildfire-prone regions, each configured to detect and eradicate embers on-site;
• (bc) each AISNM comprising an onboard AI Engine (AEOB) and a plurality of miniaturized environmental sensors configured to detect wildfire precursors and combustion products, including embers, smoke, and associated chemical signatures;
• (bd) each FEM operatively attached to an AISNM and configured to instantaneously activate and spray extinguishing agents selected from cold dense mist, foam, or other fire-suppressing materials upon detection of embers;
• (be) upon detection of an ember, the AISNM configured to issue an alert, transmit a signal to an edge server, and activate all preselected AISNM/FEM units within a designated wildfire risk zone defined by a Wildfire Spread Risk Zone Prediction Engine (WSRZPE);
• (bf) the WSRZPE configured to generate and update a geospatial wildfire spread zone surrounding the ignition site;
• (bg) an edge server deployment module configured to launch a fleet of autonomous drones, including Autonomous Inspection Drones (AID), Autonomous Eradication Drones (AED), and Autonomous Prevention Drones (APD);
• (bh) each AED configured with fire-extinguishing payloads and programmed to autonomously navigate to the ignition site and high-risk zones designated by the WSRZPE;
• (bi) each AISNM further configured to initiate local eradication and transmit alerts to the edge server and nearby AISNM units, enabling coordinated and autonomous wildfire prevention;
• (bj) post-eradication deployment, AIDs are launched to verify the complete absence of embers, flames, or smoke, after which the system issues a fire-extinguished confirmation;
• (bk) launch of APDs to apply fire-retardant materials to the perimeter and surrounding areas of the extinguished zone, operating in fully autonomous mode Independent surrounding areas of the extinguished zone, operating in fully autonomous mode.

An Artificial Intelligence Sensing Network Module (AISNM) comprising:

• (bl) a physical enclosure housing an onboard AI processing module (AEOB), an autonomous intelligent network module (AINM), a plural of sensors, battery and a memory module, wherein the enclosure is compact, shoebox-sized or smaller, and configured for mounting on trees, drones, or utility poles;
• (bm) a plurality of environmental detection sensors operably connected to the AI module, the sensors comprising at least one of:
• Lidar, 2D or 3D high-resolution video imaging systems, thermal imaging sensors, particle counters, spectrometers, electromagnetic wave sensors, miniature ion chromatography systems, ion-selective electrodes, atomic absorption spectroscopy (AAS), inductively coupled plasma (ICP) analyzers, mass spectrometers, colorimetry instruments, microelectromechanical system (MEMS) thermal sensors including microbolometers or thermopiles, photoionization detectors (PID), electrochemical gas sensors, air ion counters, UV and IR sensors, and gas-specific sensors;
• (bn) the sensors are configured to detect wildfire-indicative parameters including, but not limited to, smoke dispersal, ember movement, elevated ion concentrations, UV and IR radiation, thermal signatures, spectral characteristics of ionized gases, and thermally reactive chemical compounds;
• (bo) the AI module configured to perform time-series analysis on real-time sensor data to label anomaly events corresponding to wildfire ignition indicators, including abrupt changes in temperature, particle velocity, ion concentration, or particulate movement;
• (bp) the AISNM further configured to stream real-time data related to temperature, humidity, 3D imagery, and ultra-high-resolution particulate analysis including particulate density, direction, material composition, and velocity;
• (bq) wherein the onboard AI module is further configured to analyze the visual, thermal, and spectral signature of embers and smoke prior to ground contact, with contextual correlation to weather, temperature, and wind direction;
• (br) upon positive identification of wildfire precursors, the AEOB is operable to trigger the Fire Extinguishing Module (FEM), issue alerts, notify adjacent AISNM units and edge servers, and initiate automated suppression protocols;
• (bs) upon confirmation that the fire has been extinguished, the AEOB is further configured to transmit a termination signal to adjacent AISNM units and edge servers to revert from active suppression to passive monitoring mode;
• (bt) the AISNM unit is engineered to be self-sustaining, comprising an integrated power supply system including a solar panel, battery pack, and maximum power point tracking (MPPT) controller for autonomous off-grid operation;
• (bu) the enclosure comprises physical properties including flame resistance, heat insulation, UV and weather protection, electromagnetic shielding, lightweight structural materials, and rugged durability for forest and rural deployment;
• (bv) the AISNM unit is communicatively coupled with other AINM units of the Next Generation Autonomous Intelligent Communication Network (NGAICN), and is configured to propagate alerts and activation commands to neighboring modules in regions determined to be at risk of fire propagation;
• (bw) the AISNM unit is further configured as a secondary-layer NGAICN node comprising a low-bandwidth LEO satellite communication module AINM and an antenna footprint of 1 square foot or smaller, and wherein said node is operable to extend NGAICN coverage over an additional 20-30 mile radius to support coordination with hundreds or thousands of downstream AISNM/FEM clients;
• (bx) Upon validation of an emerging wildfire event by any AEOB within the network, all associated AISNM units and their respective Fire Extinguishing Modules (FEM) are automatically activated to release eradication materials in a coordinated manner, thereby collectively suppressing identified wildfire precursors and extinguishing the emerging fire at once.

A Next-Generation Autonomous Intelligent Communication Network (NGAICN) for operation in areas including remote, forested, and previously unreachable Areas, comprising:

• (cp) A self-sustaining, layered, and modular intelligent communication and power network that can operate in areas where connections were previously unreachable;
• (cq) A distributed satellite receiver operatively coupled to an Autonomous Intelligent network module (AINM) contained in AISM or Drones configured to receive satellite signals through a satellite dish or small devices in rural or historically connection-deprived areas;
• (cr) The AINM/AISM module comprises multiband components and software defined Radios that transform the satellite band into commonly used transmission formats, including 5G, 4G LTE, radio and more;
• (cs) NGAICN uses Low orbital Leo Satellite as back haul and transmits its signal stream near ground in low band, middle band or high band networks depending on the local environment and end user type and usage;
• (ct) NGAICN's end user comprises, cell phone, devices, other AINMs, AISM, servers, gateways, IoT, Wi-Fi modems, and more;
• (cu) NGAICN provides end users with routine data communication, internet access, voice, facility, device monitoring, or other usage, including IoT;
• (cv) The low band 4G LTE NGAICN communication network )provides coverage in a radius of 15 to 30 miles and is capable of penetrating dense vegetation, including forested areas;
• (cw) Each intelligent AINM node service has the capability to cover hundreds or thousands of users or device nodes within a 15-30-mile area;
• (cx) Each AINM module is equipped with a satellite dish and device, enabling it to upload and download data packages to and input from other users on the same or different networks;
• (cy) The AINM/AISNM is configured to dynamically upgrade to mid-band and high-band frequencies, including 5G/6G, LTE, and Band 14, or any other frequencies upon detection of fires or embers;
• (cz) NGAICN's communication policy excludes using high-orbit satellite systems and conventional extremely low data rates such as LoRaWAN and basic radio systems, due to insufficient bandwidth, data rate limitations, and lack of compatibility with 5G and FirstNet emergency protocols;
• (da) The NGAICN comprises distributed multilayer dynamic node management:
• (i) Layer 1:
• user or intelligent modules;
• (ii) Layer 2:
• Multiband intelligent communication AINM module layer;
• (iii) Layer 3:
• The regional node layer comprises the network of AINMs in the region;
• (iv) Layer 4:
• The super node layer comprises all the regional nodes in a country;
• (v) Layer 5:
• Comprise all the nodes in the enterprise;
• (db) The AISNM may be operated as a second-layer node with a small, low-band Leo satellite dish (1×1 feet or smaller) and an AINM module;
• (dc) During an emergency, the AINM/AISNM modules will autonomously switch to provide 5G/6G full-band services, enabling the full radio streaming of ember movement, thermal images, UV/IR visual data, and sensor statistical data, thereby facilitating an efficient autonomous eradication process;
• (cd) The NGAICN satellite set up on Drone Station and FCCC comprises a Layer 3 regional layer with wideband, fast 5G/6G services, and is capable of fully communicating with all AISNM modules, central, satellite, and edge servers, providing internet and Voice access;
• (de) an FCCC and drone station infrastructure, are equipped with LEO satellite antennas configured to provide high-reliability, high bandwidth internet backhaul, which is then converted into localized terrestrial communication services independent of ground infrastructure;
• (df) At the FCCC, the received satellite signal is converted into broadband 5G/6G or 4G LTE, including Band 14, to support the system, server management, and first responders' operations;
• (dg) An AI-driven emergency communication upgrade mechanism, wherein an onboard AI engine (AEOB) detects embers, smoke, or thermal anomalies;
• triggering the immediate transition from routine mode to active emergency mode and initiates FirstNet or equivalent high-speed data channels for real-time video transmission, AI analysis, and command coordination;
• (dh) NGAICN is a multilayer, dynamic node management system that enables NGAICN to be used in various countries with different policies and security concerns, making internet connections in previously inaccessible areas;
• (di) a renewable power supply system, wherein all communication and sensor units are powered by solar or wind energy, managed by maximum power point tracking (MPPT) controllers achieving greater than 95% power efficiency.