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The need to design buildings with due consideration for bioclimatic and passive design is central to promoting sustainability in the built environment from an energy perspective. Indeed, the energy and atmosphere considerations in building design, construction and operation have received the highest consideration in green building frameworks such as LEED and BREEAM to promote SDG 9: Industry, Innovation and Infrastructure and SDG 11: Sustainable Cities and Communities and contributing directly to support SDG 13: Climate Action. The research literature is rich of findings on the efficacy of passive measures in different climate contexts, but given that these measures are highly dependent on the prevailing weather conditions, which is constantly in evolution, disturbed by the climate change phenomenon, there is pressing need to be able to accurately predict such changes in the short (to the minute) and medium (to the hour and day) terms, where AI algorithms can be effectively applied. The dynamics of the weather patterns over seasons, but more crucially over a given season means that optimum response of building envelope elements, specifically through the passive elements, can be reaped if these passive measures can be adapted according to the ambient weather conditions. The use of representative mechatronics systems to intelligently control certain passive measures is presented, together with the potential use of artificial intelligence (AI) algorithms to capture the complex building physics involved to predict the expected effect of weather conditions on the indoor environmental conditions.

Although a basic need, housing and its development activities impinge on the environment. As part of efforts to promote sustainability, there have been several initiatives since the Brundtland Commission's work in 1987 to minimise the adverse impact of housing development activities on the environment in the developing world such as sub-Saharan Africa (SSA). This chapter explores housing development activities in Ghana within the context of environmental sustainability based on the extant literature. The aim is to examine the state and promotion of environmental sustainability in the housing development sector. The chapter establishes that although there are some efforts to promote environmental sustainability within the housing development sector, uptake of environmental sustainability practices has been less satisfactory due to lack of incentives as stakeholders perceive that environmentally sustainable homes are more expensive than conventional ones. The chapter, therefore, recommends further investigations into the cost and benefit of environmentally sustainable homes as well as other drivers in Ghana to give additional insights to provide the appropriate doses of incentives both contrived and instinctive to drive uptake.

The United Nations (UN) sustainable development goals (SDGs) that became effective at the commencement of January 2016 constitute a global community agreement calling for action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity. This chapter looks at the nexus between real estate (RE) and SDGs by investigating the extent to which Ghana's RE sector incorporates, especially, environmental sustainability principles from the design and construction stages to occupation, operation and activities aimed at helping to solve the problem of climate change, thereby, contributing to achieving the SDGs. The chapter is theoretical and, therefore, heavily reliant on critical review of relevant extant literature. The chapter has shown that RE cuts across virtually all the sectors that contribute greenhouse gas (GHG) emissions, which over the years have generally been increasing. Only a few buildings in both the private and public sectors (six located in three of the 16 administrative regions in the country) are officially classified as green based on three sustainability-rating systems currently used in the country, which suggests that the uptake of green building technologies (GBTs) is rather low leading to the conclusion that at the moment, the RE sector is not contributing much towards the attainment of the SDGs. However, it may be the case that there are buildings, which are sustainable in one form or the other, but because they have not been officially certified, they are not regarded as green – employing the services of the sustainability-rating agencies to certify buildings involve significant costs that might serve as a barrier in accessing their services. Thus, there is the need for country-wide, large-scale studies that systematically investigate the uptake of GBTs in the private and public RE sectors (not necessarily based on using the rating systems) as that may reveal the actual uptake of GBTs and what can be done policy-wise based on the outcomes of such studies.

Following Philip Selznick’s lead in using pragmatist social science to understand issues of public concern we conducted a study of failed innovation in the commercial construction industry (CCI). We find that social heuristics – collectively constructed and maintained interpretive decision-making frames – significantly shape economic and non-economic decision-making practices. Social heuristics are the outcome of industry-based “institutionalization processes” and are widely held and commonly relied on in CCI to reduce uncertainty endemic to decision-making; they provide actors with both a priori and ex post facto justifications for economic decisions that appear socially rational to industry co-participants. In the CCI – a project-centered production network – social heuristics as shared institutions sustain network-based social order but in so doing discourage novel technologies and impede innovation. Social heuristics are actor-level constructs that reflect macro-level institutional arrangements and networked production relations. The concept of social heuristics offers the promise of developing a genuinely social theory of individual economic choice and action that is historically informed, contextually situated, and neither psychologically nor structurally reductionist.

This chapter compares the current biodiversity practices of higher education institutions (HEIs) and their learning effects of the Global North and South. It particularly explores the HEIs’ strategies targeting biodiversity and ecosystem services preservation. In order to answer the research question, a qualitative content analysis of published sustainability reports of the systematically selected HEIs was performed. The Times Higher Education (THE) was used to select HEIs. The results show that biodiversity reporting and management is still in its early stages in HEIs from both the Global North and South and could benefit from further research and suggestions for improvement. One implication for the HEIs is that they could increase public awareness and knowledge of biodiversity through the integration of this topic into their curricula, more research projects on biodiversity, and operations on and off campus.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything smarter than ever. IoT leads to a network of things which creates a self-configuring network. Improving farm productivity is essential to meet the rapidly growing demand for food. In this chapter, the authors have introduced a smart greenhouse by integration of two leading technologies in the market (i.e., Machine Learning and IoT). In proposed model, several sensors are used for data collection and managing the environment of greenhouse. The idea is to propose an IoT and Machine Learning based smart nursery that helps in healthy growing and monitoring of the seed. The structure will be a dome-like structure for observation and isolation of an egg with various sensors like pressure, humidity, temperature, light, moisture, conductivity, air quality, etc. to monitor the nursery internal environment and maintain the control and flow of water and other minerals inside the nursery. The nursery will have a solar panel from which it stores the electricity generated from the sun, a small fan to control the flow of air and pressure. A camera will also be equipped inside the nursery that will use computer vision technology to monitor the health of the plant and will be trained on the past data to notify the user if the plant is diseased or need attention.

This chapter describes the results of an exploratory study that examined parents’ experiences with the law as they obtained funding for speech generating devices for their children with communication disabilities, either through public health insurance, private health insurance, or a public school. Exploring legal consciousness: Experiences of families seeking funding for assistive technologies for children with disabilities. Law, Policy, and Society Dissertations. Paper 17. Retrieved from http://hdl.handle.net/2047/d20000265). The study explored how parents engaged with the law and how their experiences and perceptions about the law compared to the formal law. This research was based on sociolegal theory, particularly the concept of legal consciousness, which examines how people think and act in relation to the law as a consequence of social interactions, and analyzes how law in action compares with the formal law. Sociolegal theory broadens the definition of law to include “the meanings, sources of authority, and cultural practices” (Ewick & Silbey, 1998, p. 22) as well as the formal law.

Similar to other sociolegal research, this study collected personal narratives of law using grounded theory methods to identify themes within those narratives. The narratives revealed that while parents expressed varieties of legal consciousness, there was one overarching theme: the law provided a framework for parents to envision rights, discuss rights, and claim rights. While few parents invoked formal legal mechanisms to solve grievances, the law created a rights consciousness among parents which empowered them to acknowledge and validate the notion of rights and entitlements.