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A large body of evidence has confirmed that the indoor air pollution (IAP) from biomass fuel use is a major cause of premature deaths, and acute and chronic diseases. Over 78% of Sri Lankans use biomass fuel for cooking, the major source of IAP in developing countries. We conducted a review of the available literature and data sources to profile biomass fuel use in Sri Lanka. We also produced two maps (population density and biomass use; and cooking fuel sources by district) to illustrate the problem in a geographical context. The biomass use in Sri Lanka is limited to wood while coal, charcoal, and cow dung are not used. Government data sources indicate poor residents in rural areas are more likely to use biomass fuel. Respiratory diseases, which may have been caused by cooking emissions, are one of the leading causes of hospitalizations and death. The World Health Organization estimated that the number of deaths attributable to IAP in Sri Lanka in 2004 was 4300. Small scale studies have been conducted in-country in an attempt to associate biomass fuel use with cataracts, low birth weight, respiratory diseases and lung cancer. However, the IAP issue has not been broadly researched and is not prominent in Sri Lankan public health policies and programs to date. Our profile of Sri Lanka calls for further analytical studies and new innovative initiatives to inform public health policy, advocacy and program interventions to address the IAP problem of Sri Lanka.

This chapter discusses the relationship between small farmers land use and deforestation, with particular attention paid to the past 30 years of Amazonian colonization in Brazil and Ecuador. Our analysis calls attention to common features uniting different social groups as small farmers (e.g., social identity, access to land and resources, technology, market and credit), as well as the variability between small farmers in terms of time in the region (from native populations to recent colonists), contribution to regional deforestation, types of land use systems. At a regional level, small farmers contribute to the majority of deforestation events, but ate responsible for only a fraction of the total deforested area in Amazonia. We discuss three misconceptions that have been used to define small farmers and their contribution to the regional economy, development, and deforestation: (1) small farmers have backward land use systems associated with low productivity and extensive deforestation and subsistence production, (2) small farmers contribute to Amazonian deforestation as much as large farmers, and (3) small farmers, particularly colonist farmers, follow an inexorable path of deforestation unless curbed by government action. We conclude the chapter discussing their growing regional importance and the need for more inclusive public concerning infrastructure and services and valorization of resources produced in rural areas of Amazonia.

Agriculture is a critical domain, where technology can have a significant impact on increasing yields, improving crop quality, and reducing environmental impact. The use of renewable energy sources such as solar power in agriculture has gained momentum in recent years due to the potential to reduce the carbon footprint of farming operations. In addition to providing a source of clean energy, solar tracking systems can also be used for remote weather monitoring in the agricultural field. The ability to collect real-time data on weather parameters such as temperature, humidity, and rainfall can help farmers make informed decisions on irrigation, pest control, and other crop management practices. The main idea of this study is to present a system that can improve the efficiency of solar panels to provide constant power to the sensor in the agricultural field and transfer real-time data to the app. This research presents a mechanism to improve the arrangement of a photovoltaic (PV) array with solar power and to produce maximum energy. The proposed system changes its direction in two axes (azimuth and elevation) by detecting the difference between the position of the sun and the panel to track the sun using a light-dependent resistor. A testbed with a hardware experimental setup is designed to test the system’s capability to track according to the position of the sun effectively. In the end, real-time data are displayed using the Android app, and the weather data are transferred to the app using a GSM/WiFi module. This research improves the existing system, and results showed that the relative increase in power generation was up to 52%. Using intelligent artificial intelligence techniques with the QoS algorithm, the quality of service produced by the existing system is improved.

At this time, efforts are being made on a worldwide scale to accomplish sustainable development objectives. It has, thus, now become essential to investigate the part of technology in the accomplishment of these Sustainable Development Goals (SDGs), as this will enable us to circumvent any potential conflicts that may arise. The importance of wastewater management in the accomplishment of these goals has been highlighted in the study. The research focuses on the role of fourth industrial revolution in meeting the Sustainable Goals for 2030. Given that water is the most important resource on the planet and since 11 of the 17 Sustainable Goals are directly related to having access to clean water, effective water management is the most fundamental need for achieving these goals. The age of Industry 4.0 has ushered in a variety of new solutions in many industrial sectors, including manufacturing, water, energy, healthcare, and electronics. This paper examines the present creative solutions in water treatment from an Industry-4.0 viewpoint, focusing on big data, the Internet of Things, artificial intelligence, and several other technologies. The study has correlated the various concepts of Industry 4.0 along with water and wastewater management and also discusses the prior work carried out in this field with help of different technologies. In addition to proposing a way for explaining the operation of I4.0 in water treatment through a systematic diagram, the paper makes suggestions for further research as well.

The world population is on the rise, which demands higher food production. The reduction in the amount of land under cultivation due to urbanization makes this more challenging. The solution to this problem lies in the artificial cultivation of crops. IoT and sensors play an important role in optimizing the artificial cultivation of crops. The selection of sensors is important in order to ensure a better quality and yield in an automated artificial environment. There are many challenges involved in selecting sensors due to the highly competitive market. This paper provides a novel approach to sensor selection for saffron cultivation in an IoT-based environment. The crop used in this study is saffron due to the reason that much less research has been conducted on its hydroponic cultivation using sensors and its huge economic impact. A detailed hardware-based framework, the growth cycle of the crop, along with all the sensors, and the block layout used for saffron cultivation in a hydroponic medium are provided. The important parameters for a hydroponic medium, such as the concentration of nutrients and flow rate required, are discussed in detail. This paper is the first of its kind to explain the sensor configurations, performance metrics, and sensor-based saffron cultivation model. The paper discusses different metrics related to the selection, use and role of sensors in different IoT-based saffron cultivation practices. A smart hydroponic setup for saffron cultivation is proposed. The results of the model are evaluated using the AquaCrop simulator. The simulator is used to evaluate the value of performance metrics such as the yield, harvest index, water productivity, and biomass. The values obtained provide better results as compared to natural cultivation.