Bangladesh is shockingly feeling the fallout of climate change, which is being experienced worldwide. Living in a mostly low-lying geographical area, Bangladesh is on the front lines of coping with floods, sea-level rise, and ever-more-frequent natural hazards. Yet, in a besieged nation, hope persists. Machine learning (ML) integration has the potential to be a veritable boon-opportunity for climate change mitigation and drugs to cure some of the most challenging issues facing our country.
This is a branch of artificial intelligence where computer generate result from data without needing to be explicitly programmed. The higher processing capability can analyze masses of info at a rapid and accurate rate, making it very useful in understanding and acting to issues related to climate.
Agriculture is one of the most critical areas in Bangladesh where machine learning can be applied. Climate change is a threat to crop production, and the economy in Zimbabwe is agriculture-based. Farmers can use machine learning algorithms to predict the weather, adjust irrigation accordingly and know when to plant which crops. For example, in the Barisal region, satellite images and machine learning algorithms were used to predict monsoon patterns earlier this year. Farmers could then decide on the timing of this planting using the predictions made for the coming season, which allowed them to have better growth and, hence, yield more while also minimizing loss during monsoon months.
Machine Learning Similarly, machine learning has powerful potential for disaster preparedness and response. Cyclones and flooding occur in Bangladesh year on year. These algorithms can recognize patterns from historical occurrences (data) and make predictions for future happenings of the same kind. Bangladesh Meteorological Department recently started implementing machine learning to enhance its ability to forecast cyclones. This powerful technology will enable more precise forecasting, enabling communities to be better prepared and save lives as well as minimize property damage.
Machine learning could also be utilized to carry out better environmental monitoring and conservation efforts. Rampant deforestation and loss of habitat in Bangladesh, one of the world's most densely populated nations. Researchers can track land use and forest degradation by analyzing satellite images using machine learning. This data can aid in conservation efforts to save vital ecosystems. Another project in the Sundarbans mangrove forest used machine learning to monitor changes in forest cover where, before, time and cost constraints prevented targeted conservation efforts from being made for this particular environment.
However, the possibilities of machine learning are vast and go beyond these. It can predict energy demand and optimize the use of solar and wind resources, which is key to manage renewable energy. Since Bangladesh has ambitions to harness more of its power from renewable resources, machine learning can lead to an efficient utilization of these resources which is essential for a sustainable energy future.
Nevertheless, there are several challenges that need to be addressed before machine learning can become successfully integrated into climate change mitigation agendas. Greater investment in technology and infrastructure, additional training for local researchers and practitioners. These partnerships between government agencies, NGOs and academic institutions can bring about innovation and expand the reach of machine learning benefits.
What is more, In addition to all that This includes enabling the public at large about how powerful these technologies can be. To the extent that communities are aware they can engage in ML-based discussion of climate change and participate, they see a place for themselves in mitigation efforts. Graduate education programs that carefully balance the science of climate change and technology (e.g., climate informatics) can contribute to a more prepared public.
The potential of machine learning is, therefore, enormous in Bangladesh for climate change mitigation. The country could leverage this new technology to maximize agricultural productivity, improve disaster response and help conserve its diverse ecosystems. In the face of the magnificent tree, as Bangladesh sets its course through a maze of climate change frameworks like NAPs and NDCs, more solutions like ML will add immense value to the nation in developing both resilience and sustainability. The road ahead will not be easy, but with hard work and working together, the country can lead to a solution to combat climate change.
Fayazunnesa ChowdhuryTeacher, Department of CSE Daffodil International University PhD Research Fellow University Grants Commission of Bangladesh(UGC)
