Oil Spills are inevitable. However we try, nothing is hundred percent efficient and Oil Spills will occur. But what we can do is clean this spill at the right time in the most efficient manner. Oil spills are of different types and different oils get spilled at different circumstances. So, our project senses this spill/leak at the right time with the help of AI Sensors and turns on an alerts system and deploys drones simultaneously. These drones use laser fluorosensor and image sensing to identify the type of oil and the area of spread. Then underwater robots are used to suck in the oil (water included) and this oil is sent for further separation and Purification according to its Type and Characteristics. The advantage of using Laser Fluorosensor - remote sensing is that it works very efficiently during day time as well as during the Night. In conclusion, This Project helps to identify and clean an oil spill in the most efficient way.
Oil is one of the world's most important energy sources. It is transported by ships across the oceans and pipelines across the land due to its uneven distribution. As a result, several accidents have occurred while transporting oil to vessels, breaking pipelines, and drilling in the earth's crust.
Oil degrades the insulating ability of fur-bearing mammals, such as sea otters, as well as the water repellency of bird feathers, exposing these creatures to the elements. Birds and mammals will perish from hypothermia if they lack the ability to repel water and insulate themselves from cold water.
WORKING PHASE 1:
When an oil spill happens the sensors send alerts with the help of AI sensors.
The Sensing system works as Follows: Oils flow through pipelines. Sensors are added at Regular intervals throughout the Pipelines to monitor the flow of the oil. The Speed, Volume and Pressure of the oil is calculated between the sensors. If there is a leakage, a variation is observed in any of these characteristics. So, when there is a change of speed, pressure, etc in the flow from one sensor to another, we can easily detect that there is a Leakage in that particular area of the Pipe.
WORKING PHASE 2:
Drones are sent from ships and images are captured by remote sensing LASER FLUOROSENSOR. They capture images and detect the type of oil that is spilled. This information is passed to the server.
LASER FLUOROSENSOR works day and night.
Certain compounds, such as aromatic hydrocarbons, present in petroleum oils absorb ultraviolet laser light and become electronically excited. This excitation is quickly removed by the process of fluorescence emission, primarily in the visible region of the spectrum. By careful choice of the excitation laser wavelength and range-gated detection at selected emission wavelengths, petroleum oils can be detected and classified into three broad categories: light refined, crude or heavy refined.
WORKING PHASE 3:
Water robots are released and then oil with water is extracted. Then oil is separated from water by extracting oil according to density,this oil can be reused further. sample of oil extraction, these robots extract oil according to density and water is released out, oil is reused.
MARKETING ANALYSIS
Clean up cost takes 2.4 billion to 9.4 billion dollars which was later calculated from previous oil spills as it is impossible to calculate the estimate during oil spill. By law, the parties responsible for the use, transportation, storage, and disposal of hazardous substances and oil are liable for costs. This liability applies to the cost of containment, cleanup, and damages resulting from a release related to their own activities. However it seems, it is a complete loss for the manufacturer. Thus adapting our solution is the best way to minimize their loss and increase their profit in the long run. We are aiming for an international marketing solution. So with the help of existing technology we focus on improving marine life by early prevention of damages caused due to oil spills.
SUMMARY
Given the growing concern about marine oil spills and their consequences, we present to you a new solution based on existing technology: a software that detects oil spills and automatically grants access to drones and robots using artificial intelligence. As a result, we hope to be a new solution to a massive problem.
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Clone git repo
$ git clone "https://github.com/SREELAKSHMISUD/OIL-SPILL-SOLUTION.git"
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Create virtual env
$ pip install virtualenv
$ python -m venv env
$ ./env/Scripts/activate
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Import Modules
$ pip install keras
$ pip install pillow
$ pip install numpy
$ pip install tensorflow
$ pip install opencv-python
$ pip install virtualenv
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Execute prediction model
$ python ./main.py
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Run stremlit app
$ streamlit run .\imgpredict.py
Before running your project,make sure to run the following commands:
1.flutter pub get
2.flutter packages pub run build_runner build --delete-conflicting-outputs
This creates the generated code necessary for the project to run.
WHAT WOULD THE ECONOMIC COST OF AN OIL SPILL BE? https://twnsacredtrust.ca/concerns/economic-cost-oil-spill/
The Modem M64 is a two-way half-duplex 64bps acoustic modem with a robust and user configurable data link,which is used as a communication medium between the sensors: https://twnsacredtrust.ca/concerns/economic-cost-oil-spill/
number of oil spills per year: https://drive.google.com/file/d/1Ae3rkUGBvjlG6Fsul5UnGf8yAIWvpvXA/view?usp=share_link
Different type and sizes of tanker vessels: https://www.maritimeoptima.com/blogdata/different-type-and-sizes-of-tanker-vessels
Laser Fluorosensors: https://inis.iaea.org/search/search.aspx?orig_q=RN:35072646 https://www.sciencedirect.com/science/article/pii/B9781856179430100073
cost for water robots: https://www.americanscientist.org/article/the-robot-ocean-network#:~:text=The%20most%20advanced%2C%20but%20also,as%20deep%20as%206%2C000%20meters
Supppose there is a small amount of leakage. The alert system is set on and the amount of flow is indicated using an intensity bar. As planned, the drones are deployed and the type of oil and the amount of flow is mapped. Then the required amount of water robots are sent.
1.Flutter Flow
2.Firebase
3.Google Teachable Machine
4.Tensorflow
5.Keras
6.Python Modules
7.1 - 7.5 Million
https://drive.google.com/file/d/1IF-xhjixV5gDF9j_ZXcYMHWFdLb3gGmi/view?usp=sharing