Intelligent energy and ecosystem for real-time monitoring of glaciers

Kimothi, Sanjeev; Singh, Rajesh; Gehlot, Anita; Akram, Shaik Vaseem; Malik, Praveen Kumar; Gupta, Anish; Bilandi, Naveen

doi:10.1016/j.compeleceng.2022.108163

Cited by 28 publications

(4 citation statements)

References 22 publications

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“…There are a number of ways that AI can be applied in ecology, including the analysis of large datasets, the development of predictive models, and the identification of patterns and trends in environmental data (Christin et al 2019, Tabak et al 2019, Barlow and O'Neill 2020, Wen et al 2021, Stupariu et al 2022). For example, AI can be used to analyze satellite imagery and other remote sensing data to identify and map ecosystems (Abdollahi and Pradhan 2021, Maurya et al 2021, García‐Pardo et al 2022, Kimothi et al 2022), track the movement and behavior of animals (Sridhar et al 2019, Mathis and Mathis 2020, Smith and Pinter‐Wollman 2021), and monitor the health of forests and other natural habitats (Kinaneva et al 2019, Liu et al 2021, Maurya et al 2021, Kimothi et al 2022). AI can also be used to develop predictive models that can forecast the impacts of climate change and other environmental factors on urban and natural ecosystems (Huntingford et al 2019, How et al 2020, Chakraborty et al 2021, Dewitte et al 2021, Luccioni et al 2021), as well as to identify patterns and trends in the data that can inform conservation and management efforts (How et al 2020, Dewitte et al 2021).…”

Section: Exploring the Role Of Ai In Ecology: Improved Chatgpt Perspe...mentioning

confidence: 99%

Artificial Intelligence in Ecology: A Commentary on a Chatbot's Perspective

Haghighi

Saqalaksari

Johnson

2023

Bulletin Ecologic Soc America

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The potential of artificial intelligence (AI) to shape research and education is a highly topical issue. The recent release of ChatGPT (Chat Generative Pre‐trained Transformer) by OpenAI on November 30, 2022 has opened up new possibilities for the use of chatbot services in ecological research and education. In this perspective article, we address associated contemporary topics including the use of chatbot services in ecology education and academic writing, the application of AI in ecology, the potential environmental impact, and ethical considerations of using such services. Several logistical, ethical and environmental factors were identified that should be considered in the context of ecological research. We argue that ChatGPT can help reduce the workload of researchers, generate new insights and ideas, and serve as a personal instructor and assistant for students. While we show how AI chatbots have the potential to be useful assets for ecologists, several challenges arose. AI in ecological research includes the limited ability of AI algorithms to capture complexity and nuance, the dependence of AI models on data quality, and ethical concerns about the use of AI in research. The construction and operation of such services also have potential environmental impacts but may also provide environmental benefits in comparison with other conventional approaches, all of which should be evaluated. Despite these limitations and challenges, we consider that the use of AI can be a valuable tool in ecological research and could enhance the speed and efficiency of research by automating certain tasks (e.g. data collection and management) and analyzing large amounts of data. However, we emphasize the importance of taking a responsible, sustainable and transparent approach to using chatbot services and AI in ecological research and education, while remaining mindful of the potential impact on the environment, society, and ethical concerns.

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Section: Exploring the Role Of Ai In Ecology: Improved Chatgpt Perspe...mentioning

confidence: 99%

Artificial Intelligence in Ecology: A Commentary on a Chatbot's Perspective

Haghighi

Saqalaksari

Johnson

2023

Bulletin Ecologic Soc America

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Section: Digitalization For Bipvmentioning

confidence: 99%

“…(a) IoT: IoT was first proposed at the end of the twentieth century, and it was developed using radiofrequency technology [20,21]. The GSMA estimates that the number of IoT connections will reach 25 billion worldwide by 2025 [22,23]. IoT is a collection of devices with embedded systems connected to the internet's telecommunications network with the ability to generate and send data without the need for human interaction.…”

Section: Digitalization For Bipvmentioning

confidence: 99%

Building Integrated Photovoltaics 4.0: Digitization of the Photovoltaic Integration in Buildings for a Resilient Infra at Large Scale

et al. 2022

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Building integrated photovoltaic (BIPV) systems have gained a lot of attention in recent years as they support the United Nations’ sustainable development goals of renewable energy generation and construction of resilient infrastructure. To make the BIPV system infra resilient, there is a need to adopt digital technologies such as the internet of things (IoT), artificial intelligence (AI), edge computing, unmanned aerial vehicles (UAV), and robotics. In this study, the current challenges in the BIPV system, such as the rise in the temperature of the PV modules, the occurrence of various faults, and the accumulation of dust particles over the module surface, have been identified and discussed based on the previous literature. To overcome the challenges, the significance and application of the integration of these digital technologies in the BIPV system are discussed along with the proposed architecture. Finally, the study discusses the vital recommendations for future directions, such as ML and DL for image enhancement and flaws detection in real-time image data; edge computing to implement DL for intelligent BIPV data analytics; fog computing for 6G assisted IoT network in BIPV; edge computing integration in UAV for intelligent automation and detection; augmented reality, virtual reality, and digital twins for virtual BIPV systems with research challenges of real-time implementation in the BIPV.

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“…One such subject could be anthropogenic global climate change (usually referred to in the vernacular as global warming), which is widely publicized in popular media and considered by most scientists to be one of the most pressing environmental problems facing the modern world (e.g., Oreskes, 2004; Marlon et al, 2019). Unfortunately, most professional research on this topic requires techniques and/or resources that are beyond the reach of middle and high school students, and even typical undergraduates (e.g., examination of oceanic uptake of carbon dioxide (CO 2 ) [Tsunogai et al, 1999; Ballantyne et al, 2012], computer modeling of climate change [Edwards, 2001; Hausfather et al, 2022], and satellite monitoring of glacier change [various papers in Chuvieco, 2007; Kimothi et al 2022])…”

Section: Introductionmentioning

confidence: 99%

A Class Project for Investigating Possible Future Local Effects of Global Climate Change through Student Analysis of Fossil Faunas

Lambert

2023

The American Biology Teacher

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A common question posed to environmental scientists by nonscientists, particularly policymakers, is the following: In a world that is globally warmer, what will the new climate be like in specific geographical regions? This question has been and continues to be addressed by computer modeling, a technique that is out of reach for vast majority of students. However, an alternate approach to investigating this issue exists that is more practical for students. Past climates can be inferred for specific regions from fossils, utilizing climate tolerances of related modern organisms. When these inferred past climates correspond to periods of the Earth’s history where levels of carbon dioxide were as high or higher than today, these data can be used to extrapolate possible future local climates in a globally warmer world. The last Pleistocene interglacial period (known as the Eemian), which occurred approximately 120,000 years ago, is an ideal time period for studies of this kind for the following reasons. First, carbon dioxide levels were elevated at this time to levels approximating modern global conditions, and the world was warmer as evidenced by a much higher sea level than exists today. Secondly, most Eemian-age animals (especially mollusks) still exist, have known climate tolerances, and are relatively common as fossils. Students examining fossil mollusk faunas have applied this methodology to infer the Eemian climates of South Florida and coastal Virginia and found unexpectedly that for both regions the Eemian climate did not greatly differ from the modern one. The methodology described here can be used to address other important questions and puts such authentic and potentially valuable scientific research within practical reach of student scientists.

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Intelligent energy and ecosystem for real-time monitoring of glaciers

Cited by 28 publications

References 22 publications

Artificial Intelligence in Ecology: A Commentary on a Chatbot's Perspective

Artificial Intelligence in Ecology: A Commentary on a Chatbot's Perspective

Building Integrated Photovoltaics 4.0: Digitization of the Photovoltaic Integration in Buildings for a Resilient Infra at Large Scale

A Class Project for Investigating Possible Future Local Effects of Global Climate Change through Student Analysis of Fossil Faunas

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