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In this chapter, a general introduction on artificial intelligence (AI) is given as well as an overview of the advances of AI in different engineering disciplines, including its effectiveness in driving the United Nations Sustainable Development Goals (UN SDGs). This chapter begins with some fundamental definitions and concepts on AI and machine learning (ML) followed by a classification of the different categories of ML algorithms. After that, a general overview of the impact which different engineering disciplines such as Civil, Chemical, Mechanical, Electrical and Telecommunications Engineering have on the UN SDGs is given. The application of AI and ML to enhance the processes in these different engineering disciplines is also briefly explained. This chapter concludes with a brief description of the UN SDGs and how AI can positively impact the attainment of these goals by the target year of 2030.

Connected machines are the automation of several types of machines connected towards beneficial growth of sustainable construction especially in the era of the Fourth Industrial Revolution. This chapter gave an insight into the emergence of digitalisation in the construction sector and the importance of connected machines in sustainable construction. It further elucidated its mode of operations, devices applicable, drivers and challenges for its full application in construction and benefits on construction projects. It finally gave a conclusion on its urgent need for full incorporation due to its technological benefits for present and future construction works.

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

It is now well-established that good water quality is associated with economic prosperity, reduced incidence on public health and the good functioning of the various ecosystems found in our environment. Water contamination is mostly related to both diffused (agricultural lands and geologic rock degradations) and point sources of pollution. Mauritius has many water resources which depend solely on precipitation for their replenishment. Water parameters which are of relevance include total dissolved solids (TDS), temperature, pH, electrical conductivity, turbidity, dissolved oxygen, dissolved and particulate organic carbon and major cations and anions. The traditional methods of analysis for these parameters are mostly using electrical and optical methods (probes and sensors in the field), while chemical titrations, Flame AAS and High-Performance Liquid Chromatography techniques are carried out in the laboratory. Image Classification techniques using neural networks can also be used to detect the presence of contaminants in water. In addition to basic water quality parameters, the field sensors range have been extended to cover important major ions and can now be integrated with Artificial Intelligence (AI)-based models for the prediction of variations in water quality to better protect human health and the environment, reduce operation costs of water and wastewater treatment plant unit processes.

Alain Bouchard was born in 1949. He bought his first convenience store in 1978, when he was almost 30 years old. By then, he already had nearly 10 years of experience in the sector. He had already been involved in the start-up of more than 200 convenience stores. He understood that if he was to transform his newly acquired store into a chain and build something big, he needed to set up a team of people with complementary skills to help him make acquisitions.

In 2023, there are roughly 15,000 convenience stores operating under the Circle K/Ingo/Couche-Tard banners, employing 130,000 people in more than 30 countries. Annual sales are more than US$60 billion. Alain Bouchard officially retired from his position as President and CEO in 2014 and became Founder and Executive Chairman of the Board. He continues to be a major shareholder. He is still actively involved in strategic orientations and in identifying potential acquisitions. He has become a ‘Chief Culture Officer’ involved in executive leadership mentoring. He has never stopped communicating the importance of innovative, creative and intrapreneurial behaviour at all levels of the enterprise.

This case study presents Alain Bouchard, the man and the entrepreneur. It shows how he learned and mastered the craft of starting, acquiring, managing and developing convenience stores. It looks at how he encouraged the people around him to act as facilitators and intrapreneurs. It describes his values, how he works and learned to live with risk.