WO2019244094A1

WO2019244094A1 - Wildfire detection system and method using array of co2 sensors and artificial intelligence

Info

Publication number: WO2019244094A1
Application number: PCT/IB2019/055209
Authority: WO
Inventors: João LADEIRA
Original assignee: Ladeira Joao
Priority date: 2018-06-20
Filing date: 2019-06-20
Publication date: 2019-12-26
Also published as: WO2019244094A4

Abstract

The present invention relates to a wildfire detection system that uses an array of CO₂ sensors (2) and artificial intelligence. This system comprises a sensorial unit (1), a gateway (G) to relay sensorial unit data to a designated server (R) and a software (S) with a designed algorithm for processing the incoming data and trigger the fire alarms whenever it is necessary. In another aspect, the present invention relates to a method of detecting an environmental fire in its early stage by using the system described herein. Therefore, the present invention is in the domain of electronic devices for detection of environmental fires.

Description

DESCRIPTION

WILDFIRE DETECTION SYSTEM AND METHOD USING ARRAY OF C0₂

SENSORS AND ARTIFICIAL INTELLIGENCE

TECHNICAL DOMAIN OF THE INVENTION

The present invention relates to a wildfire detection system that uses an array of CO2 sensors and artificial intelligence. This system comprises a sensorial unit, a gateway to relay sensorial unit data to our servers and a software with a designed algorithm for processing the incoming data and trigger the fire alarms whenever it is necessary.

In another aspect, the present invention relates to a method of detecting an environmental fire in its early stage.

Therefore, the present invention is in the domain of electronic devices for detection of environmental fires.

BACKGROUND OF THE INVENTION

There are several wildfire detection technologies available today. The three most used technologies are camera-based systems, satellite-based systems and sensor array-based systems. The present invention is an improvement on the latter. Currently, sensor array-based systems can only detect small wildfires in less than 30 meters thus making such solution very expensive to implement and install. Furthermore, they are powered by lithium-ion batteries that presents a safety risk as well as an environmental risk. Lithium-ion batteries over time can leak chemicals to the nature, as well as they can in some rare cases explode and themselves provoke the fire. Another limiting aspect of most state-of-the-art systems is the communication distance of less than 500 meters; this also limits large scale implementation of such system as it will have an even higher price tag, and as well increase base stations installation efforts.

Document CN203606917U describes a wildfire detection system with a smoke sensor, short range radio and a rechargeable battery. However, since it doesn't contain a long-distance low power radio, temperature sensor, humidity sensor and a supercapacitor limit's this solution in both fire detection, communication distance and redundancy as well as in safety of the solution. Since it uses rechargeable batteries and those contain chemicals inside, it presents an environmental hazard in case of leaks in the batteries. Also smoke sensor is very generalist, there are various ways to detect smoke with different types of sensors and or a combination of them.

Document CN201780647U describes a wildfire detection system with a slow response C02 sensor, GSM radio, temperature sensor and rechargeable battery. However, since it doesn't contain a long-distance low power radio, humidity sensor, a fast response C02 sensor and a supercapacitor this solution is limited in both fire detection, communication distance and redundancy as well as in safety of the solution. Since it uses rechargeable batteries and those contain chemicals inside, it presents an environmental hazard in case of leaks in the batteries. A response time of 2 min of the TGS4160 C02 sensor makes this very slow to detect fires where every second counts, also power consumption of this solution makes it an impractical and very large solution, needing even more batteries that can contaminate even more it's surrounding environment.

Document US7142105B2 describes a wildfire detection algorithm and sensors using linear regression fitting with CO and C02 sensors .

The present invention proposes a system and a method for detecting wildfires that overcome the drawbacks of the known solutions allowing to detect an environmental fire in its early stage and to provide adequate solutions to extinguish it in a fast and efficient manner.

SUMMARY OF THE INVENTION

The present invention relates to a wildfire detection system that uses an array of CO2 sensors and artificial intelligence.

This system comprises a sensorial unit, a gateway to relay sensorial unit data to our servers and a software with a designed algorithm for processing the incoming data and trigger the fire alarms whenever it is necessary according to claim 1.

Detecting wild land fires in the very early stages is crucial in order to save lives, control and combat the fire before it becomes uncontrollable. A global and efficient view of the entire fire and its parameters is also necessary in order to quickly make hard decisions, for instance on where to concentrate the firefighting force, thus ending the fire as soon as possible.

Current solutions available in the market are either too costly, complex, hard to maintain, hard to install and prone to false alarms or a combination of above. In order to have a widespread adoption the system needs to be efficient, reliable, cheap and easily deployed to cover as much area as possible and lower the false positives and false negatives close to zero .

For this purpose, the present invention relates to the development of a system and a method that is able to detect wildfires in their very early stages effectively and efficiently using one or more ambient sensorial units that send ambient data wirelessly using LPWAN technology. This data is analysed in real-time by adequate artificial algorithms on the back-end servers. After data is processed, alarms can be triggered and viewed on an intuitive user interface.

This system is safer than state of the art solutions, this is because the system primarily uses a supercapacitor that does not have any chemicals that can leak to the forest, as well as can withstand higher and lower temperatures.

Therefore, in another aspect, the present invention relates to a method of detecting an environmental fire in its early stage according to claim 12.

DESCRIPTION OF THE FIGURES

Figure 1 represents a preferred embodiment of a sensor case from side perspective, top side is attached to a tree branch and sensor can be adjusted horizontally by adjusting the screws, wherein:

1. Sensorial unit

8. Energy harvest unit - a solar panel (8a) Figure 2 represents a preferred embodiment of a sensor case from bottom perspective, a protective grid is applied to protect sensor against small animals and protecting it from the external environment, wherein:

1. Sensorial unit

11. Air influx passageway

Figure 3 represents a preferred embodiment of a sensor case from bottom perspective without the protective grid and air influx passageway, wherein:

2. CO2 sensor

3. Temperature sensor

4. Humidity sensor

5. LPWAN radio

7. Microcontroller

Figure 4 represents a preferred embodiment of a sensor case from side perspective in "exploded view", wherein:

2. CO2 sensor

3. Temperature sensor

4. Humidity sensor

5. LPWAN radio

6. Energy storage unit -, a super capacitor (6a)

7. Microcontroller

9. Protective grid

10. PCB cover GENERAL DESCRIPTION OF THE INVENTION

The present invention relates to a wildfire detection system and method that uses an array of CO2 sensors and artificial intelligence. This system comprises a sensorial unit, a gateway to relay sensorial unit data to our servers and a software with a designed algorithm for processing the incoming data and trigger the fire alarms whenever it is necessary.

1. Fire detection system

The system of the present invention comprises at least a sensorial unit (1), a gateway (G) and a software (S) with a designed algorithm for processing the incoming data and that is able to trigger a fire alarm in its very early stage whenever it is necessary.

Each sensorial unit (1) comprises at least a CO2 sensor (2), a temperature sensor (3), a humidity sensor (4), a LPWAN radio (5), an energy storage unit (6), a microcontroller (7), an energy harvesting unit (8), and all passive and active electronic components (E) that are required for its functioning.

These elements are integrated in a software (S) with artificial intelligence algorithms and LTSM networks and allow the early detection of wildfires as well as accurate warning of danger zones before even fire starts, in case of natural causes.

For that purpose, the several sensorial units (1) are spread throughout the desired area, monitoring a maximum distance of 1 Km, being at most 2 Km apart from each other. Gateways (G) are positioned on the field on strategic positions in order to maximize communication distance and redundancy of the desired area. They are placed at most 30 Km apart from each other and in higher grounds whenever possible, in order to maximize transmission and reception signal.

Software (S) stack and corresponding servers can be hosted in any part of the world and communicate with the gateways (G) in order to get incoming data.

This communication can be done with any kind of communication carrier such as GSM, satellite, cable or any kind of state- of-the-art data transport. Sensorial units (1) connect with the gateways (G) using a star network topology.

The main advantages provided by this system are the following:

• Long distance communication that allow to reduce network costs;

• Use of a supercapacitor for the energy storage unit for safer operation;

• Use of the CO2 sensor as main reactor for detecting fire;

• Use of temperature and humidity together with anemometers to enhance raw data and improve prediction accuracy;

• Use of artificial algorithms to extract all features from raw data coming from sensors and interpret them;

• Low power design;

• Autonomous .

The purpose of a sensorial unit (1) is to be able to measure the surrounding ambient and send its data to a server (R) even remotely for further processing in real time and/or deferred. It is also equipped with a LPWAN radio (5), an energy storage unit (6) and an energy harvesting unit (8) . The energy storage unit (6) and energy harvesting unit (8) are ideally a supercapacitor (6a) and a solar panel (8a) respectively .

By using a supercapacitor instead of a normal lithium battery, the risk of the sensorial unit catching fire on its own is reduced or even eliminated. Supercapacitors can also withstand higher and lower temperatures than the chemical battery counterpart and are generally safer.

Suitable supercapacitor to be used in the scope of the present invention are, for example low ESR EDLC (Electric double-layer capacitor) supercapacitor of 100F or even 325F with 500000 charge-discharge cycles that can withstand temperature ranges of -40 to +85°C.

The use of the supercapacitor (6a) as its energy source (6) is only possible because of the low power design of the sensorial unit (1) and the built-in energy harvesting unit

The sensorial unit (1) is capable of operating autonomously even when receiving less energy than usual through the energy harvesting unit, for example a cloudy day. EDLC (Electric double-layer capacitor) supercapacitors do not contain any chemicals, this means that they cannot leak any chemicals into their surroundings, contrary to traditional lithium-ion batteries that over time can leak chemicals into their surroundings .

Each sensorial unit (1) is able to communicate wirelessly with the gateways (G) over distances greater than 15 Km thanks to the LPWAN radios (5) . Suitable radios (5) in the scope of the present invention are LoRa radios, Sigfox radios or NB- IOT radios such as Semtech sxl276 in case of the Lora radio, which provides long distance communication with very low power usage and small footprint.

They can also sense fire within a radius of more than 1 Km depending on wind speed and direction. Since the sensorial units (1) are stationary there is no need to include a GPS module (X) on them. Instead, when installing the units (1) a fast-one-time configuration is done on the servers (R) to save its accurate position. Because of its low weight and reduced dimensions, it can be easily attached to existing trees thus eliminating the need for any third-party support hardware. One such embodiment for the case dimensions can be as little as 85x60x30 millimetres.

Sensorial units (1) communicate with the gateway (G) in two scenarios, being the first one and most common involving the periodic communication that is performed either from 5 minute intervals or more if battery saving is needed; the second scenario is when CO2 levels, temperature and humidity surpass a configurable threshold per sensorial unit; in this case raw data is sent immediately to the gateway (G) so it can be processed right away by the algorithms. In order to save energy, the sensorial unit (1) is sleeping or in standby mode most of the time. However, it periodically checks ambient data between the predefined communication intervals so that we can achieve the second scenario.

In order to prevent insects and animals to damage or reduce sensor performance, small electrostatic or electromagnetic discharge impulses can optionally be generated by the sensorial unit (1) . Gateways (G) bridge the physical world to the virtual one, receiving all data coming from the sensorial units (1) and relaying them to the servers (R) in order to be processed. They are spread out and placed strategically in a manner that ideally at least two of them pick up the signal from a sensorial unit (1) in order to guarantee some redundancy.

Gateways (G) can be also equipped also with anemometers in order to enhance data that will be sent to the back-end and predict fire direction, also using artificial algorithms. Gateways (G) can also be fully autonomous like the sensorial units (1) . Nevertheless, in order to reduce initial costs, they can be plugged to any public utility power grid.

The server (R) processes and stores the incoming data and is able to work in real time, i.e. to process the data as soon as it arrives. Artificial algorithms are able to process the incoming raw data and generate several outputs from it. With that information, it is possible to set and trigger one or more alerts to the all the configured parties as soon as a fire is detected, and send all the relevant information such as the accurate position, direction and dimensions as well as all individual values that can be interpreted by a human with more context awareness than the current algorithms.

All data can be visualized by multiple entities at the same time. Moreover, the sensorial units can be attached to the firefighter suit. By including a GPS module on it, the firefighters command centre officer can monitor the firefighters' accurate position and environmental data including CO² level, temperature and humidity, thus taking more informed decisions when planning next movements for all troops on the ground. All this information can be seamlessly visualized on an intuitive user interface.

Therefore, the present invention implements a low power, autonomous, low cost, long range system to detect, monitor and manage wildfires and its participants in all of its stages. It is also easy to install and maintain using a CO2 sensor as the main sensor combined with artificial intelligence algorithms.

In order to delay wildfire spreading speed, special drones equipped with fire extinguisher grenades can used. Drones are installed on the gateways and as soon as fire is detected by the system, they are deployed automatically and fly through fire detection location that was calculated by the system and start dropping the fire extinguisher grenades in order to delay/end with the wildfire until firefighters arrive to the place. All these operations are autonomous and do not require human intervention.

Sensorial Unit Model A

In this particular embodiment, the Sensorial Unit (1) comprises a temperature sensor (3), a humidity sensor (4) and a C02 sensor (2) . It uses an EDLC (Electric double-layer capacitor) supercapacitor (6a) of 100F as energy storage unit (6) and a 1W solar panel (8a) to charge the energy storage unit (8) when necessary .

This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 10 years. Since this model uses a supercapacitor is safer than the others and does not contain any chemicals in the energy storage unit.

Sensorial Unit Model B

In this particular embodiment, the Sensorial Unit (1) comprises a temperature sensor (3), a humidity sensor (4) and a C02 sensor (2) . It uses two NIMH batteries (6a) of 1300mAh as energy storage unit (6) and a 1W solar panel (8a) to charge the energy storage unit (8) when necessary.

This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 5 years .

Sensorial Unit Model C

In this particular embodiment, the Sensorial Unit (1) comprises a temperature sensor (3), a humidity sensor (4) and a C02 sensor (2), and a built-in GPS unit (12) in order to broadcast accurate current position in a mobile environment as well as a push button. It uses two NIMH batteries (6a) of 2800mAh as energy storage unit (6) and a 1W solar panel (8a) to charge the energy storage unit (8) when necessary.

This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 5 years. With its built-in GPS unit (12) this sensor can be tracked in real-time while in motion, this can be for example fitted in a firefighter's suit in order to track its position as well as if the firefighter is in a dangerous environment. If firefighter feels that he needs help, he can press the panic button and instantly central command will be notified if this action.

Sensorial Unit Model D

In this particular embodiment, the Sensorial Unit (1) comprises a temperature sensor (3), a humidity sensor (4) and a C02 sensor (2), and a PM2.5 sensor (particle matter 2.5 microns). It uses an EDLC (Electric double-layer capacitor) supercapacitor (6a) of 200F as energy storage unit (6) and a 1W solar panel (a) to charge the energy storage unit (8) when necessary .

This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 10 years. Since this model uses a supercapacitor is safer than the others and does not contain any chemicals in the energy storage unit. By using additional PM2.5 sensor it can more accurately confirm the presence of a fire.

Gateway Model 1.

This Unit (G) comprises a microcontroller (7), GSM transceiver a concentrator module, an external antenna, a Lead Acid battery, energy harvesting controller and a 50W solar panel. This module does the bridge between local sensors and cloud servers, re-transmitting all sensor data redundantly when using more than one gateway and different types of transports.

Gateway Model 2.

This Unit (G) comprises a microcontroller (7), a satellite transceiver , wind direction sensor, wind speed sensor, concentrator module, external antenna, four EDLC supercapacitors of 400F, energy harvesting controller and a 50W solar panel.

This module does the bridge between local sensors and cloud servers, re-transmitting all sensor data redundantly when using more than one gateway and different types of transports. This specific model transmits sensor's data to cloud servers via a satellite transceiver. It also collects wind direction and speed; these values are also sent to cloud servers to be processed by the designed algorithms. Since this model uses supercapacitors it can be charged up a lot quicker than conventional lithium-ion or lead acid batteries. It is also a lot safer because it does not contain any chemicals as well it can withstand higher temperature ranges than conventional batteries .

Gateway Model 3 .

This Unit (G) comprises a microcontroller (7), wind direction sensor, wind speed sensor, concentrator module, external antenna, four EDLC supercapacitors of 400F, energy harvesting controller and a 50W solar panel. In the gateway platform, a drone is ready to be deployed.

This module does the bridge between local sensors and cloud servers, re-transmitting all sensor data redundantly when using more than one gateway and different types of transports. This specific model transmits sensor's data to cloud servers via a satellite transceiver. It also collects wind direction and speed; these values are also sent to cloud servers to be processed by our algorithms. Since it uses supercapacitors this model can charge up a lot quicker than conventional lithium-ion or lead acid batteries. It is also a lot safer because it does not contain any chemicals as well it can withstand higher temperature ranges than conventional batteries. A standby drone is ready to be deployed in case of a fire, delaying or even extinguishing the early wildfire, while responsible authorities are being deployed.

2. Method for detecting and alert fires

The method of the present invention uses a fire detection system comprising an array of CO2 sensors and artificial intelligence. This method uses the system of the invention as described above, which comprises a sensorial unit (1), a gateway (G) to relay sensorial unit data to a designated server (R) and a software (S) with a specifically designed algorithm for processing the incoming data and trigger the fire alarms as described above.

When there is a fire ignition:

1) The ambient data in the sensorial unit (1) starts to change, in the most common scenario, humidity decreases, C02 and temperature values increase;

2) The sensorial unit (1) finds that a predetermined and pre set ambient pattern is formed;

3) The sensorial unit (1) transmits in real time this information in the form of values to the servers in order for them to be evaluated with more precision;

4) A designated server (R) processes received ambient data with dedicated algorithms in order to confirm that a fire was indeed detected;

5) If fire was detected, data related to it such as fire location, type of fire, direction, is calculated using various information collected by the sensorial units, such as position, wind direction, wind speed, sensorial unit ambient readings and others;

6) An alarm is sent to the interested party, indicating fire position and other relevant information;

Optionally, drones with fire extinguishing grenades are deployed from nearby gateways in order to extinguishing or control de fire.

In this way the fire can be monitored constantly by system, indicating fire current direction and speed, as well as predicted direction and speed using gateways built-in wind speed and direction sensors, as well as sensorial units' information and dedicated algorithms.

After fire is extinguished a message is sent to the interested party in order to inform that the fire has ended and information about drone maintenance, such as refill grenades and other types of damage drones might have sustained.

EXAMPLES

Example 1. Sensorial Unit type 1

In this example, the Sensorial Unit comprises of an integrated environmental sensor BME680 from Bosch Sensortec that integrates a temperature, humidity, barometric pressure, VOC and eC02 sensors inside it. An EDLC (Electric double-layer capacitor) supercapacitor of 100F, the Maxwell BCAP0100 P270 S07 ultracapacitor is used as energy storage unit and a 1W solar panel to charge the energy storage unit when necessary. A Semtech sx!276 LoRa radio is used for its communication module. This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 10 years. Since this model uses the Maxwell BCAP0100 P270 S07 ultracapacitor as its energy storage unit and is significantly safer than batteries as it does not contain any chemicals in its energy storage unit and can withstand temperature ranges of -40 to +85 degrees Celsius. Response time of this unit is less than 1 second and energy storage unit is capable of 500000 charge-discharge cycles which again is significantly better than conventional batteries that can only do between 500 to 1000 charge-discharge cycles. Unit shell was carefully designed to maximize air flow direction right into sensor area and computational simulations as well as real world tests were performed in order to maximize sensor performance. Thanks to its radio, the Semtech sxl276it can communicate with the nearest gateway at a distance of more than 15 Km with line of sight.

Example 2 . Sensorial Unit type 2

In this example, the Sensorial Unit comprises an integrated high accuracy temperature and humidity sensor from Texas Instruments, the HDC2080 as well as a low power VOC sensor from AMS, the CCS811 Gas Sensor, capable of eC02 measurements. An EDLC (Electric double-layer capacitor) supercapacitor of 325F, the Maxwell BCAP0325 P270 S17 ultracapacitor is used for its energy storage unit and a 1W solar panel to charge the energy storage unit when necessary.

This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 10 years. Since this model uses the Maxwell BCAP0325 P270 S17 ultracapacitor as its energy storage unit and is significantly safer than batteries as it does not contain any chemicals in its energy storage unit and can withstand temperature ranges of -40 to +85 degrees Celsius. Response time of this unit is less than 1 second and energy storage unit is capable of 500000 charge-discharge cycles which again is significantly better than conventional batteries that can only do between 500 to 1000 charge-discharge cycles. Thanks to its radio, the Semtech sxl276it can communicate with the nearest gateway at a distance of more than 15 Km with line of sight.

Example 3 . Sensorial Unit type 3

In this example, the Sensorial Unit comprises an integrated high accuracy temperature and humidity sensor from Texas Instruments, the HDC2080 as well as a low power VOC sensor from AMS, the CCS811 Gas Sensor, capable of eC02 measurements. This unit uses two NIMH batteries of 1300mAh for its energy storage unit and a 1W solar panel to charge the energy storage unit when necessary. Thanks to its radio, the Semtech sxl276it can communicate with the nearest gateway at a distance of more than 15 Km with line of sight.

Example 4 . Sensorial Unit type 4

In this example, the Sensorial Unit comprises an integrated high accuracy temperature and humidity sensor from Texas Instruments, the HDC2080 as well as a low power VOC sensor from AMS, the CCS811 Gas Sensor, capable of eC02 measurements as well as a built-in GPS unit in order to broadcast accurate current position in a mobile environment. Uses four NIMH batteries of 2800mAh for its energy storage unit and a 1W solar panel to charge the energy storage unit when necessary.

This model is capable of detecting wildfires at distances of up to 1 Km while consuming very low energy. Its solar panel gives it permanent energy for its lifetime that can be more than 5 years. With its built-in GPS unit this sensor can be tracked in real-time while in motion, this can be for example fitted in a firefighter's suit in order to track its position as well as if the firefighter is in a dangerous environment. If firefighter feels that he needs help, he can press the panic button and instantly central command will be notified if this action. Thanks to its radio, the Semtech sxl276it can communicate with the nearest gateway at a distance of more than 15 Km with line of sight .

Example 5. Sensorial Unit 5

In this example, the Sensorial Unit comprises an integrated high accuracy temperature and humidity sensor from Texas Instruments, the HDC2080 as well as a low power VOC sensor from AMS, the CCS811 Gas Sensor, capable of eC02 measurement as well as a PM2.5 sensor, the Honeywell HPMA115S0-XXX. It uses an EDLC (Electric double-layer capacitor) supercapacitor of 325F, the Maxwell BCAP0325 P270 S17 as its energy storage unit for its energy storage unit and a 1W solar panel to charge the energy storage unit when necessary. Thanks to its radio, the Semtech sxl276it can communicate with the nearest gateway at a distance of more than 15 Km with line of sight.

Gateway Model 1.

This Unit (G) comprises a microcontroller, a concentrator module, an external antenna, a Lead Acid battery, energy harvesting controller and a 50W solar panel.

Gateway Model 2.

This Unit (G) comprises a microcontroller, wind direction sensor, wind speed sensor, concentrator module, external antenna, four EDLC supercapacitors of 400F, energy harvesting controller and a 50W solar panel.

Gateway Model 3 .

This Unit (G) comprises a microcontroller, wind direction sensor, wind speed sensor, concentrator module, external antenna, four EDLC supercapacitors of 400F, energy harvesting controller and a 50W solar panel. In the gateway platform a drone is ready to be deployed.

Claims

1. A fire detection system having at least a sensorial unit (1), a gateway (G) for relaying the sensorial unit data to a designated server (R) and a software package (S) with a designed algorithm for processing the incoming data and that is able to generate reports and triggering a fire alarm characterized by each sensorial unit (1) comprising one or more of the following elements: a CO2 sensor (2), a temperature sensor (3), a humidity sensor (4), a LPWAN radio (5), an energy storage unit (6), a microcontroller (7), an energy harvesting unit (8), and all passive and active electronic components (E) that are required for its functioning integrated with artificial intelligence algorithms and LTSM networks.

2. A fire detection system according to claim 1 characterized by the software package (S) with a designed algorithm comprising different parameter settings for trigger a fire alarm in function of said parameters such as CO2, temperature and/or humidity levels.

3. A fire detection system according to claim 1 or 2 characterized by the software (S) with a designed algorithm being located in one or more remote servers (R) .

4. A fire detection system according to claim 1 characterized by the energy storage unit (6) being a supercapacitor (6a) and/or the energy harvesting unit (8) being a solar panel (8a) .

5. A fire detection system according to any of the claims 1 to 4 characterized by the sensorial unit (1) further comprising a "particle matter 2.5 sensor".

6. A fire detection system according to any of the claims 1 to 5 characterized by the sensorial unit (1) comprising a GPS unit.

7. A fire detection system according to any of the claims 1 to 6 characterized by the sensorial unit (1) comprising a generator of electrostatic or electromagnetic discharge impulses .

8. A fire detection system according to any of the claims 1 to 7 characterized by the gateway (G) comprising a wind sensor unit capable of sensing the wind direction and wind speed .

9. A fire detection system according to any of the claims 1 to 8 characterized by the sensorial units (1) being positioned in the intended area to be monitored for fire occurrence, having a maximum distance between them of 1 km of radius apart, preferably the maximum distance is of 750m, more preferably the maximum distance is of 500m, even more preferably the maximum distance is of 250m.

10. A fire detection system according to any of the claims 1 to 9 characterized by the sensorial units (1) being positioned on the suits of individuals.

11. A fire detection system according to any of the claims 1 to 10 characterized by further comprising drones equipped with fire extinguish grenades.

12. A method for fire detection and fire alert running in a fire detection system as described in any of the claims 1 to 11, said method comprising the following steps:

a) The sensorial unit (1) collects the environmental data coming from the different sensors of the system, at least the data from a CO2 sensor (2), a temperature sensor (3) and a humidity sensor (4);

b) The collected data is processed and evaluated by the software pack (S) and compared with a predetermined and pre-set pattern values;

c) When level of CO2, temperature and/or humidity is higher than a pre-set value, raw data is sent to a gateway (G) to be processed and evaluated by the designated algorithm;

d) Then, the dedicated algorithm can confirm whether a fire is to be ignited or is already initiated; e) If confirmed, data related to the fire is generated by the software pack (S), namely the fire location, type of fire, direction, intensity in function of the input data from the several sensors of the sensorial unit

( D ;

f) A fire alarm is generated and sent to the relevant party for decision and action.

13. A method for fire detection and alert according to claim 12 characterized by the communication between the sensorial units (1) and the gateways (G) occur in three different scenarios: (i) a monitoring pre-alert mode, wherein said communication occurs every 1 to 10 minutes interval, preferably every 3 to 7 minutes interval, even more preferably every 5 minutes interval, (ii) an alert mode, wherein said communication occurs in real time, and (iii) a monitoring post-alert mode, for monitoring the evolution of the fire, also in real time until the fire is extinct or the instruction to return to mode (i) is given.

14. A method for fire detection and alert according to any of the claims 12 or 13 characterized by deployment of drones with fire extinguish grenades along with the triggering of the fire alarm.