Environmental Informatics

Environmental Informatics is one of the emerging interdisciplinary knowledge domains which is also considered as a practicing field. This is the merger of domain Environmental Science with Information Science. Environmental Informatics is dedicated in information technology and computing applications in wide areas of Environment, Ecology, and Biodiversity Management. The role of  Information Technology is emerging  day by day and its results enhancement in Environment indirectly worthy for some of the other subjects such as Geology, Geography, Climatology, Oceanography, Agriculture, Forestry. According to the experts, the stakeholders of Environmental Informatics are IT, computing, and similar technologies from the technology side dedicated in effective environmental systems organization, management, and development. Environmental Informatics is associated with the management aspects and thus also worthy in environmental management. This chapter is conceptual in nature with the basics, features, and nature of the Environmental Informatics with the role in sustainable development practice. This chapter also illustrated the technologies involved for real practice with potential academic degrees and programs in this field.

Technology is an enabler of the implementation of various strategies in solving environmental problems. Information communication and computation technology (ICCT) and nanotechnology (NT) are two new emerging general-purpose technologies that have the capabilities to solve many problems of society in an innovative and effective manner. These technologies have potentiality to manage the natural environment and ecology of the earth to support sustainable living creatures. In this chapter, we made a detailed analysis of the role of ICCT underlying technologies in environmental and ecological management for maintaining sustainable living systems on earth. The chapter discusses the technology interventions and management of natural environmental and ecology and identifies the role of ICCT underlying technologies in environmental and ecological management. The chapter also discusses implementation strategies of use of ICCT underlying technologies in environmental and ecological management and analysis of the possible role of ICCT in ecological management using a qualitative ABCD analysis framework.

Organisations are more than ever reliable on the extensive use of computing resources for their businesses. This has become more prominent with the pandemic situation of COVID-19. Many enterprises have been compelled to re-engineer their ways of doing business. They needed to turn towards information and communication technology to maintain their businesses. These have caused the use of computing resources to increase significantly among businesses. Many of them are looking forward to use computing devices in order to improve in terms of productivity and quality of products and services they offered. As a means of avoiding crowds, many of them are proposing online services. Others are making use of appointment booking systems so that customers do not have to queue for services at their offices. This is causing a significant increase in the use of computing resources, and this trend will surely continue to brighten the businesses. On the other hand, very little attention is being paid to the impact of computing on the environment. Lead, chromium and mercury in computer devices produce harmful chemicals that contaminate air and water in the environment. Computer accessories such as laser printers comprise toner particles that can affect the lungs. Prolonged use of computers promotes global warming. Computer parts are not biodegradable and are not recycled with the absence of disposal techniques. As there is much concern regarding the carbon footprint generated by computing resources, green initiatives must be encouraged at the level of the businesses. Green computing focuses on the effective design, efficient development, usage and disposal of computers together with its associated systems with minimal impact to the environment. The scope of green computing covers energy efficiency to the use of hazard-free systems. Almost every organisation has multiple computing devices. These devices are heavy consumptions of amounts of megawatts. Promoting the use of computers, servers and tablets that are energy efficient is now critical. New computing devices come on the market almost every day. Temptation to acquire the latest technology is high, and organisations must get rid of unwanted computing and electronic devices. There is a crucial need to devise appropriate disposal and recycling procedures for these unwanted devices. Green computing is a responsible use of computers and their resources in the environment. Green computing practices include the deployment of appropriate green knowledge to employees, efficient energy consumption computers, the use of energy harvesting technologies in data centres, dematerialisation with reduction of the use of paper-based documents together with enhanced disposal and recycling methods. This chapter focuses on the practice that organisations should put forward to achieve green computing initiatives.

Green Information Centre is an emerging concept of the information centre, and it is required for the modern information system practice. It is supported with the green and eco-friendly approach and dedicated in the designing, development, management and evaluation of the information systems. Eco-friendly tools, techniques and principles are considered worthy in Green Information Centre over the traditional information centre operation. Green Information Centre is not only the institutions having information solutions but also the applications of the green principles to the allied institutes where information practice is considered as worthy. Once environment-friendly green principal and systems are practised in the traditional documentation, then the establishment is known as Green Information Centre. Such types of information centres are called as sustainable information centre with integrated approach of intelligent concept in environmental management. In addition to the computing and IT, in Green Information Centre the aspects of management science, information studies, information management, etc. are highly associated with green knowledge management. The libraries and similar knowledge resource centres are also these days adopting eco-friendly principles, and this chapter discusses various aspects of Green Information Foundations in brief manner. Here, basic features and functions of the green and eco-friendly information-related foundations are discussed with emphasis on Green Libraries.

An ever-evolving environment is a constant on our planet Earth. Our economic and social well-being is influenced by the environment. People have been attempting to manipulate the environment since the dawn of technology in a variety of ways. When we try to control the environment, it just sails away. Humans have come to realize that regulating the environment is impossible since nature always finds a way to get its own way. Humans, on the other hand, have evolved ways for predicting the environment’s behavior by monitoring abrupt changes in the paraments and making essential calculations. Computers have taken over the majority of the computations, and artificial Inelegance algorithms have taken over the prediction systems, over time. However, the quality of the information utilized to make an informed decision is critical to protecting our environment. In today's environmental protection, computers play an important role in duties including monitoring, data processing, and communication. AI approaches have had a profound effect on environmental decision support systems’ conception and development. Many articles were analyzed and categorized in order to uncover answers that already exist related to the impact of the environmental changes. Access to dynamic environmental information may be gained using GeoWeb APIs. In order to bring processing to the data, cloud computing and array-friendly databases would be helpful. Geotagging and location sensing will help convert citizen scientists into environmental data collectors. The usage of a combined cycle steam power plant for electricity generation has been observed. When looking at the environmental effect, a thorough investigation is necessary. Acidification potential (AP) was determined to have the greatest influence, with NOx being the most significant cause. On-site energy consumption data were gathered, which included the amount of power used by each piece of equipment and each structure. This study examines the link between the organizational context and the development of dynamic capacities in the setting of environmental unpredictability. Economic tools from poultry farms to the production of consumer goods all rely heavily on environmental monitoring. Additionally, IoT and blockchain have a significant impact on environmental monitoring and prediction. Open-data sources that contain a wide range of environmental information may be utilized for a number of environmental analytical objectives, which in turn can have a positive impact on human well-being in the long run. An example of this can be the system that replicates the water quality in Moscow’s rivers and canals. A neural network was trained to classify a condition as either good or bad based on the data it received from the indicators. Using AI framework, policymakers, researchers, and innovators may make educated decisions on the potential and problems posed by recent changes in the environment. Authors believe that AI-based prediction systems can help humans achieve steady economic and societal goals.

Disposal of waste has become a major challenge throughout the world due to uncontrolled disposal of domestic as well as industrial wastes in open spaces. Exposure to a variety of wastes may eventually lead to the spread of various diseases and, thus, may pose serious health hazards to the public and adversely affect the environment. To minimize such issues, integrated waste management system could be a sustainable solution. It is well known that sorting of the waste at the source can be the first and the most important step to start with for efficient management of waste. This can simply be done by putting a number of labeled bins specified for each kind of wastes at the point of generation itself. However, this is the most tedious step among all the steps involved in effective waste management. To fasten the process and efficiently manage the waste collection, artificial intelligence (AI) may play a critical role in waste management which starts with the use of smart garbage bins. These bins are often combined with an app that helps the users know the availability of nearest location of the waste bins, thus preventing the bins from overflowing. AI can also play an incredible role in sorting of the wastes, as sorting is another major issue for most of the waste management facilities. AI-based sensors can discriminate items composed of different materials and distinguish the items of the same material whether an item has been chemically contaminated, ensuring purity of the waste stream. A number of waste management companies have been using such techniques and are taking the advantage of Internet of Things (IoT) sensors to monitor the fullness of trash receptacles throughout the city. The advantage of using such smart bins have effectively optimized the routes, timing and frequencies of waste collection, and reducing the load of municipalities. Such automated process would provide the best use of technology for effective waste management to prevent the human health risks as well as to protect the environment. This review article includes details on various techniques based on machine learning and the use of artificial intelligence for efficient waste management than could significantly minimize the risks associated with human health and environment.

Greenhouse farming is a closed structure for protecting the plants from extreme weather conditions such as wind, hailstorms sects, and pest attacks. The smart greenhouse improves the current agricultural practices with smart technologies for better yield. Modern technologies incur several distinct sensors to reduce the cost of inputs and improve soil productivity, conserving soil and water resources like energy. Smart irrigation in farming reduces the intake of fertilization, optimizes the growth of the crop, increases productivity, and protects the greenhouse environment. The sensors in the field acquire the measurement of soil moisture and fix the threshold level. According to the level of threshold, the water is streamed to the plants. Planning of cultivation of distinct crops in the farm can be done based on water and other nutrient requirements. Optimized planning can be achieved based on any artificial intelligence techniques. Greenhouse farm faces many challenges in irrigation such as controlling the intelligent system for dripping, sprinkling, handling the drainage problem, and waterlogging. The congestion between dripping, sprinkling and water logging can be avoided along with reduction of water wastage. Internet of Things (IoT) in smart irrigation systems with intelligent sensors will overcome the above issues by maintaining the moisture in the soil, preserving the temperature of plants. The existing sensor control irrigation system exposes the plants with controlled water deficit. Fertigation is an emerging technology in a smart irrigation system for integrating the environmental control system to optimize the level of nutrient and water management. This paper aims to deliver an optimum level of water along with nutrients to the root of the crop for reducing the wastage and evaporation of water.

According to a World Health Organization (WHO) survey, 97 percent of cities in low- and middle-income countries with over 100,000 inhabitants do not comply with WHO recommendations on air quality. Air pollution can lead to chronic and respiratory problems, such as asthma, and fatal diseases, such as lung cancer. Internet of Things (IoT) and artificial intelligence (AI) will provide tools for real-time monitoring of air pollution. The tools can identify sources of air pollution quickly and accurately. Consequently, nations around the world have raised their directions in titles of monitoring as well as regulating and handling consequent infection like COVID-19. Over the last several years, people have developed dramatically with the rush of the manufacturing revolt in which a new production of wireless communication facilitates ubiquitous connectivity among things. The recent advancement of the IoT and AI plays the major role in various enterprises. IoT is regularly perceived as practical things, broadly distributed, with low repository ability and processing potential, with the purpose of enhancing authenticity, enforcement, and preservation of the smart living and its foundations. The paper directs to a significant criterion change of how to monitor, sense, and track dynamic phenomena in real time in the environment. From this review, it is visible that there are remaining a few exciting opportunities and challenges on improvement and deployment of IoT and AI algorithms for smart and dynamic environmental monitoring.

In modern time, the e-waste generation has become one of the most serious environmental issues and difficulties to attaining long-term development. There is a pressing need for study in this area, given the potential for negative ecotoxicological consequences and a wide range of health implications. This study aims to determine the requirement for appropriate methodology, implementing basic models and approaches. In this study, an effort was made to comprehend the issues of e-waste, its production, source and destination of e-wastes, the harmful toxic contaminants present in e-wastes and their hazardous effects on human health and the environment, and the lack of collective consciousness that exacerbates the problem. A thorough investigation has been conducted into how policies may be implemented at the national, regional, and global levels to address e-waste issues. In vulnerable nations, such as developing countries in South Asia in general and India in particular, formal sequential inventory activities have been determined to be necessary. Incorporating policy implementation with an emphasis on knowledge and awareness creation has proved to be beneficial with sustainable management solutions. Furthermore, economic, environmental, and technical cooperation between high-income nations that create and supply e-waste and those that are affected by it, particularly low-income ones, might be improved. The conclusion of this study chapter is that comprehensive global e-waste management and legislation may be the best method for attaining sustainable development and mitigating the risks of e-waste.

Environmental pollution has been on the incline in the recent decades owing to expanded human movements on energy utilizations, perilous agricultural techniques, and surge in industrialization. Heavy metals, pesticides, various nuclear wastes, greenhouse emitting gases, and hydrocarbons are the well-known pollutants that cause environmental and human health problems due to their toxicity. Bioremediation pinpoint the involvement of chemical machinery in environmental decontamination of pollutants by microbial discourse or web through in situ or ex situ outcome. For degrading the pollutants, in situ process required bioaugmentation, biosparging, and bioventing while ex situ bioremediation involves composting, bioreactors, electrodialysis, land farming, and biopiling. Microorganisms utilizing hydrocarbon as the sole resource of carbon and energy have a vital role in the biodegradation of pollutants. Due to the continuous environmental variations, the microorganisms thriving in that environment are well equipped to survive. The actinomycetes, fungus, and thermophylic bacterium like microbes in different biomes have been isolated in biodegradation. With the improvement of scientific technologies, the system biology, omics (proteomics and glycomics) nanotechnology, and gene editing tools are being used in bioremediation of heavy metal pollutants, plastics, petroleum, organic pollutants, or other hydrocarbon, acid leachate, biofilm formation, and xenobiotics. System biology approaches are very promising in decoding the existence of microbial populations under varied environmental setup. Omics such as proteomics and genomics aid in analyzing genetic or protein-level regulation for bioremediation with sequencing, MALDI-TOF, and novel functional genes’ involvement in bioremediation pathways of pollutant degradation.

Internet of Things (IoT) is a modern technical method that aims to relate things represented by devices and sensors and connect them to the Internet to transfer and receive data with each other without any kind of human intervention or human supervision. It is a virtual network that combines different things classified within electronics, software, sensors, and actuators. It connects them through the Internet, which allows these things to exchange data with each other, and it was introduced at the end of 1999 by Professor Kevin Ashton. It is worth mentioning that the term “thing” in the Internet of Things is not limited to inanimate objects and small devices only, the “thing” in IoT may be a woman who is carrying a heart rate device, for example, a girl carrying a tracker device, and a car equipped with sensors and indicators. Environmental applications are also considered one of the most important areas and current and future trends of Internet of Things technology. Through the use of environmental applications of technology, human life can be greatly improved such as desalination of salty sea water, weather forecasting, wastewater refining, obtaining the highest level of agricultural crops, and many other beneficial uses of technology.

Alternative research efforts have been conducted for the last few years to overcome the deficit spectrum of electromagnetic waves which can release the network traffic from the saturated radio frequency domain. With some of the culture and development, it can be stated that optical wireless communication can lead to a new spectrum of data sharing. Consumption of data and its usage has increased more than 100 times in the last 10 years. Development of around 80 billion IOT systems has also contributed to the crisis of radio spectrum availability and increased traffic. It is forecasted that by 2022 there will be use of around 50 zettabytes of data, that can be imagined as many bits of stars and planets in the universe. With the recent contribution from researches, a new domain has been termed as visible light communication (VLC) and will reinforce the communication protocol. In this domain, the architectural transformation resulted in light fidelity (Li-Fi), replacing the wireless fidelity (WiFi) with added security and unrestricted bandwidth allocation.

There are 300 Tetra Hz unused bandwidth (1000 times 300 Giga Hz of radio frequency spectrum) available at higher frequencies in the visible light spectrum. LiFi uses the visible light spectrum for communication, which is much faster than radio frequency, and can be easily used in near field communication. Many researches have served with multiple conceptions and misconceptions in this experimental area. The technology is advancing with the speed of its own concept, visible light. Establishing the liable system and computing the data, parametrical diversity is in progress. Professor Harald Haas of Edinburgh University has provided many clear out reach for the proposed system. Many tech-giants have configured their own. But in our daily life, bringing ease to our society has been a concept and dream till now. Converging all the thought at a point with the recent development and implementation, in this chapter we claim to successfully design a light fidelity-based system, which can be used for traffic signal sensing and managing, and it will be energy efficient. As it is studied that LiFi system transmits data through LED and receives through photocell, LED is a clear source of energy-efficient output and photocell (solar cells) which absorbs light energy and converts into electrical energy is a proven energy-efficient receptor.

Our system proposes a long-range LED, which transmits light spectrum of over 1.5 km and reflects back after incident on the surface of the vehicles. Solar cells used as receptors of this light beam track the congestion of the beams. The implementation of the transmitter and receiver can be done in affordable and reliable using microcontroller like ATmega 328. The data can be retrieved and processed, and the density of vehicles can be traced, with easy controlling of the traffic signals. With amplification of the incident light beam on solar cells, it can be reused for power support to the circuitry, making it less biasing potential consuming device. The emergency vehicles can also be traced with some deviation of visible light spectrum wavelengths. This design opens up path for many researches on the field of smart city application, environment and its different parameter monitoring systems.

As the system uses LED as a source and solar panel as a receptor, it is very much energy efficient. The solar panel can charge the inbuilt battery itself and can operate in day and night condition. The conventional traffic management system uses mainly camera-oriented system, so this proposed system is quite energy efficient. After feeding the count in the edge level gateways in each of the traffic points, the traffic light may be controlled upon the policy of the city. Thus, this proposed system is quite relevant for smart city applications or smart traffic management system. This proposed system is also cost-effective as it is only using LED, small photocell (here it is solar receptor) and microcontroller ATmega 328 for deployment, and traffic control can be done through edge computing using Raspberry Pi.

COVID-19 and environmental factors were connected to an elevated risk of pre-existing diseases associated with illness severity, immune system impairment, viral survival and transport, and viral exposure-inducing behaviours. The global health calamity caused by the COVID-19 epidemic has a wide range of negative consequences in every aspects of life, which includes the environment, economy, social, political, and cultural realms. COVID-19 infestation, in the first wave with more severity and a severe disaster in our human society. Advancement in technology especially in information technology (IT) applications in disaster management has become an essential part. COVID-19 a sudden epidemic disaster in all sectors of our human society. Strategic preparedness and response plan we have taken at national and international levels to overcome the ongoing challenges in the response to COVID-19. To identify, manage, track, and care for new cases of COVID-19, all countries enhanced their preparedness, alertness, and response. The present study focussed on information technology (IT)-based control over human and monitoring of COVID-19 environment calamity.

Unmanned aerial vehicles (popularly known as drones) are being increasingly used in wildlife research. These remote-controlled devices are often used to collect information from areas which are otherwise very difficult to access by the researcher. Therefore, drones are promisingly advantageous over various traditional research techniques. Application of these technologies not only increases the accessibility but also reduces human effort and collect accurate information by causing minimal disturbance to the habitat. For these reasons, application of UAVs has gained popularity over last few decades in various domains of ecological research across the globe. In wildlife research, the UAVs are used in population surveys, dispersion studies, nest monitoring, radio telemetry studies, habitat assessment, etc. Undoubtedly, UAVs show great prospect of its application in many ecological and wildlife research in future. In such a scenario, this review is an attempt to provide the researchers with a glimpse of the remarkable progress along with the benefits and future scopes of this modern technology in various wildlife researches.

Flood is considered as the annual event in the Lower Ganga Plain. It causes adverse impact on the population in terms of economic and social life. Floodwater hampers the physical life both directly (drowning, snake bite, hypothermia, etc.) and indirectly (water and vector-borne diseases). The abundance of cutoffs and marshy lands in Uttar Dinajpur district leads to the outbreak of water-borne diseases during the monsoon and post-monsoon session. Therefore, an attempt has been made to classify the region into index-based potential waterlogging zone using the multi-criteria decision making analysis. Total eight geo-hydrological parameters were taken into consideration such as elevation, slope, relative relief, geomorphology, groundwater depth, drainage density, soil, and MNDWI. The normalized weights were assigned to the parameters using the analytical hierarchy process (AHP), constructed on their relative importance on waterlogging situations and incorporated in the GIS environment using the overlay method. Finally, the Potential Waterlogging Zone (PWZ) map was compared with the historical geo-hazard map of the concerned area for the validation of the work. The very high PWZ accounts for 66.69 km² area of the district which is mostly the perennial marshy lands, whereas the majority of the portion (1835.28 km²) comes under High PWZ mainly due to the inadequate drainage facilities during the flood discharge. Subsequently, the moderate PWZ comprises for about 1036.38 km² area which is comparatively less vulnerable to the flood related health issues. Therefore, the overall approach of the study can be used to reduce the vulnerabilities related to water infectious diseases through comprehensive surveillance, emergency health facilities, early warning system, and well-coordinated collaborations.

The qualities of different groundwater parameters rely on the sources of groundwater recharge, industrial effluent, urban interactions, agriculture, aquifer pumping, and waste disposal. Domination of any of these factors alters the groundwater quality. GIS enables the tracking of changes throughout time within an area/ watershed and correlating changes in water quality with these alterations. Choosing an appropriate GIS-spatial interpolation technique is a critical success element in surface analysis since different interpolation methods might result in different surfaces and, eventually, different outcomes. Though no particular interpolation technique is completely optimum, the best interpolation method for a given circumstance can only be determined by comparing their results. An automated tool has been developed to assess popular interpolation techniques like inverse distance weightage, radial basis function, ordinary kriging, universal kriging, empirical Bayesian kriging, and kernel interpolation in terms of root mean square error and mean absolute error. The model provides researchers and official groundwater quality monitoring and assessment teams with the help to pick the optimal algorithm.