AI in Ecological crisis
There are several problems for mankind. But, those which appear to be common to a major portion of the population are addressed as social problems. Among them, Ecological crisis is the most frightening issue at present.
The time has come. The environmental crisis has picked up the pace. The doomsday might come true if it still goes in the same manner. Since my birth, to the extent of my remembrance, I heard a lot of times about this issue. I was told by my parents and teachers to save water, electricity, food and every natural resource. I don’t know whether I did follow them but it’s not worth the discussion now.
The point to be noted is — we are in danger. The alert is because of the following symptoms:
1. Increase in global temperature.
2. The decrease in rainfall.
3. Depletion of groundwater.
4. Extinction of various species.
5. Increase in frequency of natural calamities.
6. Increase in pollution levels.
The changes in the environment of a species can destabilize its continued survival and this leads to the ecological crisis. The known causes can be deforestation, species overpopulation, global warming and instability in abiotic ecological factors.
Technology has obtained a great extent such that at least one of the things around us in every moment is a technical device. And in most of the cases, it is a smartphone. All of us use mobile applications of amazon, the e-commerce giant. The recommendations we get in the shopping website amazon.com is based on a Machine Learning algorithm called Recommender systems. The Google Assistant, Apple’s Siri, Microsoft’s Cortana, Facebook’s photo-tagging system, Amazon’s Alexa, Hike’s sticker recommendation, and many others are the products of artificial intelligence.
People in the earlier days, when the dawn hasn’t seen all these technological advancements, they didn’t have the urge for this technology to make their life easier. Still, AI help helped them to obtain such beautiful support systems and virtual assistants, through the works of a vastly enlarging open source community. But now, it’s time to have an urge to save the environment and earth, to optimize the use of natural resources, to save the species which are in danger of extinction, and thereby to save life on Earth. After all, this planet is gifted to all the living beings on it. But as so-called social animals, it is our responsibility to take the issue seriously and act accordingly. If not, then the future generations will see the polar ice caps melt completely.
Technology has always helped society when used in the right way. So, the same technology can help in this crisis too. Machine Learning is being used in environmental research and can be further extended to discover methods to avoid the countereffects of the crisis causes. Automated animal identification, performed like crowdsourced teams of human volunteers (accuracy of 96.6%) saving approximately 8.2 years of human labeling effort (over 17,000 hours) on a 3.2- million-image dataset (Norouzzadeh et al., 2017).
Another artificial intelligence-based solution is human-activity detection in the wildlife area. This can help rangers in charge of stopping poachers, illegal trespassers of wildlife territories. Two research groups are already doing this job, one in Africa( Domain Awareness System (DAS), developed by Vulcan Technology) and another in Malaysia( Protection Assistant for Wildlife Security (PAWS)). This is needed particularly to stop poaching and illegal transportation of animals(for eg. warthog hunting) and other natural resources (for eg. smuggling of red sandalwood in Southern parts of India). This can reduce deforestation and save the target species from being taken away from their habitat.
Researchers from the University of Queensland, Australia, developed a group of models that could predict deforestation in Mexico and Madagascar. The scientists fed the models with different datasets, e.g. for terrestrial eco-regions, protected areas, and population distribution. All the algorithms were extremely accurate: the statistical value “Area Under the Curve” (AUC), which equals to 1 in a perfect model, was always above 0.8 (Mayfield et al., 2017). This type of models can help us mitigate one of the main threats to our planet. A remarkable recent application of machine learning comes from the U.S., where a research group developed prediction models that could estimate the physicochemical properties of environmental chemicals. These models are available online and can be used by anyone to “make predictions on new chemical sets, improve toxicity models, and inform hazard/risk characterization” (Zang et al., 2017).
It is well said that in classical programming, we give input and rules, we obtain output, whereas, in machine learning, we obtain rules by giving output and input.
So, the characteristics of heavy rainfall and low rainfall regions may be obtained from ML models by inputting the collection of data about them(for eg. the area of forest region around the place, population density, distance from the coast, pollution rate, etc.), along with the rainfall measure. Hence, we may understand the steps to be taken to increase the percentage of rainfall. Similar models can be developed by having a better understanding of the problem. Research is also being done in many parts of the world using Machine Learning and Deep Learning in conjunction with IoT, to solve environmental hazards.
Note — A sincere request: Nothing can be completely solved by only technology. Human is the primary force behind this extent of advancement, on which we are completely relying for a majority of tasks. This can be harmful in the other way, as every coin has two sides. Health issues are persistently rising in life due to laziness that is habituated, using this tech support. Talking about the ecological crisis, we are the major cause for it and it can be solved only if we try to. India is much likely to be out of the water by 2045. Chennai is done already with it, the groundwater is depleted in almost all the city. Major cities of India are expected to face the same problem in the near future. So, please realize the gravity of the issue and start saving the resources. Save water, Save electricity, Save energy, Save life, Save earth.
Credits: Google Images, Wikipedia and UA Magazine.
