By Purvi Agarwal

Abstract 

Regardless of its limitations, researchers and practitioners have been exploring the idea of artificial intelligence in approaching global issues, the most noticeable of which is addressing environmental issues. Similarly, leveraging cutting-edge AI and automation technologies, the concept of digital public infrastructure and smart cities is a plausible mechanism to navigate environmental and climatic change. This article aims to tread upon the prospects of artificial intelligence and monitoring and evaluation to intervene with ecological challenges while exploring the interplay of digital public infrastructure and smart cities.

Introduction 

The challenges emerging due to the climate crisis and its impacts have been gaining attention in the realm of ongoing climate change. This has also paved the way towards identifying measures like the United Nations Sustainable Development Goals (SDGS) to mitigate climate-induced challenges such as poverty, environmental degradation, global warming and biodiversity loss. While it is reassuring to see the due urgency addressed to these matters, it is pivotal to evaluate the prospects in which processing, interpreting and, most importantly, learning from this data benefits and aids the pressing challenges caused by the climate crisis. The surging fields of digital public infrastructure and artificial intelligence have the potential to be sizable solutions to environmental issues. 

Harnessing AI for Current and Future Ecological Challenges 

Artificial intelligence (AI) is gaining attention in international discourse as well as in day-to-day conversations as an emergent progression in many disciplines. AI as a term was first coined at the 1956 Dartmouth Summer Research Project on Artificial Intelligence, where scientists convened to explore the possibility of building sentient machines. Since then, several methods and technologies have been developed that have allowed machines to carry out tasks previously believed to be exclusive to humans, greatly advancing the field of artificial intelligence. This has culminated in data collection, monitoring and evaluation, predictive analytics, risk analysis, agriculture and environmental conservation, media, and even academia, where machinery and software are steadfastly integrated. The World Intellectual Property Organisation (WIPO) states that AI is commonly seen as a discipline that comes under the study of computer science. 

Monitoring and data collection form the basis for a wide range of problems, regardless of our inclination to address it. Environmental monitoring and data collection can be as simple as the metre system one has in their household or, on a larger scale in a building, an apartment complex or even a group of apartment complexes in a large area. Through real-time monitoring, learning algorithms and warning systems, AI could help process and utilise the data for energy sustainability, climate change mitigation, sustainable development resource management, waste management, ecosystem Conservation and biodiversity protection. These systems can integrate and process vast amounts of data from multiple sources to provide us with a comprehensive understanding of weather stations, sensors, and remote sensing, as well as environmental conditions. 

The UNEP data catalogue, with more than 2,100 total datasets available, aims to make all environmental data easy to find, download, use and share. It also grants access to maps of geospatial data from diverse sources in the form of census data, satellite imagery and weather data. Additionally, the statistics, documentation, policy briefs and data the platform provides

provide a substantial basis for research and development. Along the same lines, the World Environment Situation Room curates, aggregates and visualises the best available earth observation and sensor data to inform near-real-time analysis and future predictions on multiple factors, including CO2 atmospheric concentration, changes in glacier mass and sea level rise. Utilising AI, monitoring and evaluation, and digital technology is also seen in the International Methane Emissions Observatory (IMEO) and the GEMS Air Pollution Monitoring platform, which have immense potential to navigate air quality management and pollution. 

Leveraging AI through Digital Public Infrastructure for Environmental Solutions and how can digital public infrastructure help in leveraging AI for environmental issues? 

In addition to several achievements and advancements that AI credits, we also see several challenges and gaps in its employment and scepticism among the general population, leading to hesitation. These include questions of ethics, biases, privacy and security, regulation, and transparency, both mainstream and specific to environmental challenges. Despite AI posing as a great solution, it comes with its limitations. The distrust is further exemplified by the usage of electrical power, which could be considered contradicting benefiting the environment in some cases. While it may take time to cultivate a one-for-all solution, digital public infrastructure (DPI) is a probable strategy to confront environmental issues, and arguably and assuredly, the interplay of DPI and artificial intelligence can be a strong prospective approach towards the same. 

Digital public infrastructure is a set of technological platforms, mechanisms or software for the general public to access and use digital spaces. The broad objective of building any infrastructure is development, which employs long-lasting methods. Understandably, any country would focus on building sustainable and inclusive digital public infrastructure, which implies considerations for energy-efficient technologies and practices. The DPI playbook is a comprehensive resource designed to guide countries in developing rights-based and inclusive digital public infrastructure (DPI). Compiled under India’s G20 presidency and the United Nations Development Programme, it sought guidelines and examples of DPI that also have or may have the scope for the interplay of AI. Expanding on the 13th Sustainable Development Goal of Climate Action, it introduces the Global Forest Watch, adopted by 25 countries, to access near-real-time deforestation data accessible through open APIs to develop custom applications. Remarkably, Namibia was the first African country to implement a carbon trading DPI and has achieved a 91% reduction in greenhouse gas emissions. 

In a smart city, the physical infrastructure, technology infrastructure, social infrastructure and business infrastructure are connected to leverage the collective intelligence of the city. Among these, the subset of energy infrastructure is perhaps the most important owing to the dependency of other infrastructure, directly or indirectly. This is why smart cities depend on smart grids, which are electrical grids with automation, communication and IT systems that can monitor power flows from points of generation to points of consumption (even down to the appliance level) and control the power flow or curtail the load to match generation in real-time or near real-time.; 

In layman’s terms, smart grids help build smart cities, which in turn are composed of DPIs. And these mechanisms only become more relevant considering that more than half of the world’s population lives in urban areas. Presumably, waste management is difficult, scarcity of resources, air pollution, health concerns, traffic mismanagement, and inadequate and ageing infrastructure need to be resolved through digital technology and an efficient, adaptive and interoperable city. In the context of smart cities, the National Industrial Corridor Development Programme’s official website states that AI can help with crowd management, estimation of size, predicting behaviour, tracking objects and enabling rapid response to incidents. It can be invaluable for managing utilities and optimising the use of resources such as distributed energy and water. AI can lead to smarter homes with resource-saving applications and ease domestic workloads. 

Ending Remarks 

The integration of artificial intelligence in daily life or policy implementation, while rapid, is still in its early stages. This compilation is meant to steer the fields of AI, environmental studies and industry experts to carefully consider the nuances of collaboration. The foundation, of course, requires a strong understanding and awareness of AI and the ecological challenges of the general population, without which it cannot be fortified. The emphasis on digital public infrastructure and smart cities remains undervalued, however, in a few cases, it stands as great instances of collaboration and mutual benefit. They provide for energy sustainability, climate change mitigation, sustainable development resource management, waste management, ecosystem Conservation and biodiversity protection. 

Author’s Bio 

Purvi Agarwal is pursuing a B.A. (HONS) in Diplomacy and Foreign Policy at the Jindal School of International Affairs and is a columnist for the Centre for New Economic Studies, Nickeled and Dimed. Apart from being the research coordinator of the Centre for European Studies, she has worked with ABP Network, the Europe India Centre for Business and Industry, the Jindal Global Centre for G20 and NDTV. Additionally, she is interested in multilateralism, Indian foreign policy and financial literacy. Purvi is proficient in Hindi and English while holding certifications in German and Japanese.

Image credits: https://www.nature.com/collections/cgcicgeabc