Other: Wildlife and forest preservation

iFireFighter

AP006

Huzaifa Saleem (National University of Science and Technology (NUST))

Nov 01, 2021 2739 views

iFireFighter

Humanity is currently facing a very major problem, something that has the potential to drastically reduce our population and ruin the lives of our future generations: Climate Change. Due to increased intensity of climate change and lack of any meaningful effort to tackle it, the corresponding problems that accompany the phenomenon of climate change are worsening year by year.

One of these problems that has set the world ablaze are forest fires. The frequency, intensity, and area affected of forest fires are steadily increasing every year. It’s like every year the California wildfires or the Australian bushfires are more intense and cause more damage than the last year’s.

Once a fire has reached critical mass and spread beyond a certain limit, it’s extremely costly, time consuming, and takes a lot of manpower and effort to get it under the control. The natural remedy for tackling this issue is to nip the problem in the bud before it has a chance to blossom.

All major wildfires and forest fires start from a much smaller localized fire that once they reach a critical mass, grow out of control. Our project proposes to detect and alert the relevant authorities about these localized fires before they grow out of control.

Fighting a fire after it has grown past critical mass is extremely costly. From the equipment to the resources to the manpower and personnel, along with the potential for an immense loss of human life, a lot of money must be thrown at the problem to get the fire back under control.

Our project would reduce these costs massively since the focus would then shift from getting a raging uncontrollable fire back under control to quickly and efficiently extinguishing a much smaller fire before it spreads.

Project Proposal


1. High-level project introduction and performance expectation

Humanity is currently facing a very major problem, something that has the potential to drastically reduce our population and ruin the lives of our future generations: Climate Change. Due to the increased intensity of climate change and lack of any meaningful effort to tackle it, the corresponding problems that accompany the phenomenon of climate change are worsening year by year.

One of these problems that hasset the world ablaze are forest fires. The frequency, intensity, and area affected by forest fires are steadily increasing every year. It’s like every year the California wildfires or the Australian bushfires are more intense and cause more damage than the last year’s.

Once a fire has reached critical mass and spread beyond a certain limit, it’s extremely costly, time-consuming, and takes a lot of manpower and effort to get it under the control. The natural remedy for tackling this issue is to nip the problem in the bud before it has a chance to blossom.

All major wildfires and forest fires start from a much smaller localized fire that once they reach a critical mass, grow out of control. Our project proposes to detect and alert the relevant authorities about these localized fires before they grow out of control.

Our idea includes dividing the area of interest into N segments, with the area of the segments being almost equal to the range of the analog sensors that we will be using for data collection. Each segment will have a data acquisition node which will consist of the relevant sensors along with an Arduino microcontroller with a GPS shield and Wi-Fi capabilities. The sensors that we plan to use are NDIR Thermopile-based Gas Sensing Circuit for monitoring of CO2 levels and Flexible, Low Power, 4-Channel Thermocouple System with Arduino-Compatible Digital Interface for temperature monitoring. The excess emissions of CO2 levels monitored by the NDIR gas sensors allow for swift detection of wildfires while the temperature sensors monitor increases in temperature reducing false alarms and allowing accurate detection of wildfires.

Each of these N nodes will send their relevant data with their location wirelessly to the FPGA board that will be used for data preprocessing and data conditioning. The data can be sent through any of the myriad wireless protocols. This will then be uploaded onto the azure cloud for processing and post-processing which will then generate an alert if there’s been a fire at some location. The intensity of the fire along with its location will be shown in azure dashboard. Using the analytics, a map will be created specifying the location of each node and the coordinates of the wildfire.

Humanity is currently facing a very major problem, something that has the potential to drastically reduce our population and ruin the lives of our future generations: Climate Change. Due to increased intensity of climate change and lack of any meaningful effort to tackle it, the corresponding problems that accompany the phenomenon of climate change are worsening year by year.

One of these problems that has set the world ablaze are forest fires. The frequency, intensity, and area affected of forest fires are steadily increasing every year. It’s like every year the California wildfires or the Australian bushfires are more intense and cause more damage than the last year’s.

Once a fire has reached critical mass and spread beyond a certain limit, it’s extremely costly, time consuming, and takes a lot of manpower and effort to get it under the control. The natural remedy for tackling this issue is to nip the problem in the bud before it has a chance to blossom.

All major wildfires and forest fires start from a much smaller localized fire that once they reach a critical mass, grow out of control. Our project proposes to detect and alert the relevant authorities about these localized fires before they grow out of control.

Our idea includes dividing the area of interest into N segments, with the area of the segments being almost equal to the range of the analog sensors that we will be using for data collection. Each segment will have a data acquisition node which will consist of the relevant sensors along with an Arduino microcontroller with a GPS shield and Wi-Fi capabilities. The sensors that we plan to use are NDIR Thermopile-based Gas Sensing Circuit for monitoring of CO2 levels and Flexible, Low Power, 4-Channel Thermocouple System with Arduino-Compatible Digital Interface for temperature monitoring. The excess emissions of CO2 levels monitored by the NDIR gas sensors allow for swift detection of wildfires while the temperature sensors monitor increase in temperature reducing false alarms and allowing accurate detection of wildfires.

Each of these N nodes will send their relevant data with their location wirelessly to the FPGA board that will be used for data preprocessing and data conditioning. The data can be sent through any of the myriad wireless protocols. This will then be uploaded onto the azure cloud for processing and post processing which will then generate an alert if there’s been a fire at some location. The intensity of the fire along with its location will be shown in azure dashboard. Using the analytics, a map will be created specifying the location of each node and the coordinates of the wildfire.

2. Block Diagram

3. Expected sustainability results, projected resource savings

The biggest resource saving that can be expected from this project is the amount of wildlife, nature, and trees and plants saved due to a proactive approach of stopping a fire before it spreads too much. Wildfires and forest fires cause an immense amount of natural damage, habitat destruction, and loss of wildlife. Considering the situation of Pakistan’s “Billion Tree Tsunami,” an out-of-control fire would also represent a very high economic loss along with rendering a lot of time and effort spent on wildlife management null and useless.

Alongside that, fighting a fire after it has grown past critical mass is extremely costly. From the equipment to the resources to the manpower and personnel, along with the potential for an immense loss of human life, a lot of money must be thrown at the problem to get the fire back under control.

Our project would reduce these costs massively since the focus would then shift from getting a raging uncontrollable fire back under control to quickly and efficiently extinguishing a much smaller fire before it spreads.

4. Design Introduction

5. Functional description and implementation

6. Performance metrics, performance to expectation

7. Sustainability results, resource savings achieved

8. Conclusion

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