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Since the handling of environmentally sensitive products requires close monitoring under prescribed conditions throughout the supply chain, it is essential to manage specific supply chain risks, i.e. maintaining good environmental conditions, and ensuring occupational safety in the cold environment. The purpose of this paper is to propose an Internet of Things (IoT)-based risk monitoring system (IoTRMS) for controlling product quality and occupational safety risks in cold chains. Real-time product monitoring and risk assessment in personal occupational safety can be then effectively established throughout the entire cold chain.

In the design of IoTRMS, there are three major components for risk monitoring in cold chains, namely: wireless sensor network; cloud database services; and fuzzy logic approach. The wireless sensor network is deployed to collect ambient environmental conditions automatically, and the collected information is then managed and applied to a product quality degradation model in the cloud database. The fuzzy logic approach is applied in evaluating the cold-associated occupational safety risk of the different cold chain parties considering specific personal health status. To examine the performance of the proposed system, a cold chain service provider is selected for conducting a comparative analysis before and after applying the IoTRMS.

The real-time environmental monitoring ensures that the products handled within the desired conditions, namely temperature, humidity and lighting intensity so that any violation of the handling requirements is visible among all cold chain parties. In addition, for cold warehouses and rooms in different cold chain facilities, the personal occupational safety risk assessment is established by considering the surrounding environment and the operators’ personal health status. The frequency of occupational safety risks occurring, including cold-related accidents and injuries, can be greatly reduced. In addition, worker satisfaction and operational efficiency are improved. Therefore, it provides a solid foundation for assessing and identifying product quality and occupational safety risks in cold chain activities.

The cold chain is developed for managing environmentally sensitive products in the right conditions. Most studies found that the risks in cold chain are related to the fluctuation of environmental conditions, resulting in poor product quality and negative influences on consumer health. In addition, there is a lack of occupational safety risk consideration for those who work in cold environments. Therefore, this paper proposes IoTRMS to contribute the area of risk monitoring by means of the IoT application and artificial intelligence techniques. The risk assessment and identification can be effectively established, resulting in secure product quality and appropriate occupational safety management.

This chapter explores how coming into contact with the narratives of environmental victims helps to develop different forms of reflexivity useful for imagining and confronting environmental crises. The generation and sharing of environmental data and of visual and narrative experiences of lived environmental harms by ‘ordinary people’ amounts to more than merely supplying robust data to fellow citizens, scientists and decision-makers. It is also a proactive claim for social and environmental justice, especially when these people are silenced or even criminalised. While forms of civic monitoring can be regarded as a contribution to environmental governance, they have instead often been labelled as ‘subversive’ or illegal practices. In this contribution, the authors explore how ‘green’ activist criminology may help in the challenge to have these voices enabled and listened. The challenge has to be taken up by developing an active listening attitude towards the voices of people (‘folk voices’) affected by/exposed to environmental harms, enhancing visual imagination and complexity about the contested notion of the environmental victim, together with new ways of taking care and a new paradigm of the ‘active victim’. In the conclusion, the authors acknowledge the potential of an art-based inquiry that is inclusive of civic imaginaries and knowledge. However, they also stress that cultural barriers and ideologies may hamper this potential. Critical attitude and integrity of any scientific approach should be sought and preserved.

The purpose of this paper is to illustrate the growing role of robots in environmental monitoring.

Following an introduction, this first considers aerial robots for monitoring atmospheric pollution. It then discusses the role of aerial, surface and underwater robots to monitor aquatic environments. Some examples are then provided of the robotic monitoring of the terrestrial environment, and finally, brief conclusions are drawn.

Robots are playing an important role in numerous environmental monitoring applications and have overcome many of the limitations of traditional methodologies. They operate in all media and frequently provide data with enhanced spatial and temporal coverage. In addition to detecting pollution and characterising environmental conditions, they can assist in locating illicit activities. Drones have benefited from the availability of small and lightweight imaging devices and sensors that can detect airborne pollutants and also characterise certain features of aquatic and terrestrial environments. As with other robotic applications, environmental drone imagery is benefiting from the use of AI techniques. Ranging from short-term local deployments to extended-duration oceanic missions, aquatic robots are increasingly being used to monitor and characterise freshwater and marine environments.

This provides a detailed insight into the growing number of ways that robots are being used to monitor the environment.

This paper aims to examines whether firms’ eco-friendly advertising claims are supported by environmentally friendly behavior.

The paper develops a game theory model to determine the circumstances under which firms’ environmental claims will be supported by the adoption of best environmental practice. Least squares regression is used to test major theoretical implications.

The theoretical model suggests that the credence good nature of un-monitored environmental claims prohibits consumer validation; firms have an incentive to advertise green but no incentive to adopt best environmental practice. Third-party monitoring transforms the game, making eco-friendly outcomes possible. Empirical models based on North American data suggest that firm profit rates are related to verifiable environmental claims and to easily accessible external ratings of environmental performance.

Unlike previous game theoretical models for similar goods, the eco-friendly outcome does not require a repeated game. The importance of the single period game is that continued patronage is not required for the firm to produce goods containing the desired attributes.

The purpose of this study is to implement environmental control systems; information and communication technologies based on user behavior for smart buildings and describe their definitions, technological advances, advantages and modern uses. It also highlights the complexity and difficulty of energy management and comfort via control devices.

This study reviews recent progress in control, information technologies, sensing and optimization in buildings and addresses the automation and environmental control systems of important parameters such as lighting, noise, temperature and humidity. It also explores the technological innovations and methods of management through sensors based on user behavior for the processes of optimization and control.

A proposed prototype has been developed by the combination of user behavior and control systems in buildings, mainly related to thermal comfort and energy use. This study addresses the development of a smart-comfort control system based on users’ behavior.

The main contribution of this study is the goal-driven development of an indoor quality apparatus for environmental monitoring data by using smart sensor systems. It can help users to monitor and control their environmental factors and provides functionalities for assessing comfortable ranges.

The purpose of this paper is to provide a review of environmental sensing technologies and applications and to consider briefly the research effort.

This paper describes environmental sensing strategies and technologies for air, water quality and other monitoring applications. It concludes with a brief overview of research.

As a consequence of legislation, a technologically diverse family of sensors are used in a wide range of portable and fixed instruments to determine numerous polluting compounds entering and present in the environment. These play a critical role in protecting the environment, maintaining public health and monitoring global phenomena such as ozone depletion and artificial global warming. There is a widespread and technologically diverse research effort.

This paper provides a detailed insight into the sensors and instruments used in environmental monitoring.

This paper aims to investigate the impact of monitoring and mentoring strategies on sustainability diffusion within supply networks through focal companies and how suppliers engage in implementing these strategies.

The paper reports on three in-depth case studies conducted with focal companies and their suppliers. An interaction approach was adopted to guide the analysis of focal companies’ strategies for implementing and diffusing sustainability in supply networks.

The monitoring strategy impacts sustainability diffusion at the dyadic level, while the mentoring strategy is a prerequisite for the diffusion of sustainability at the supply network level. The findings suggest that coupling monitoring with mentoring can lead to diffusion beyond first-tier suppliers. Interaction intensity, supplier proactiveness and mindset change facilitate sustainability diffusion in supply networks.

The authors suggest more research be conducted on specific practices within monitoring and mentoring, as some of these imply very different levels of commitment and interaction.

The paper suggests that in the future, companies will be increasingly called upon to adopt cooperative initiatives to enable the diffusion of sustainability in supply networks.

The contribution of the paper lies in its identification of the impacts of monitoring and mentoring strategies on the diffusion of sustainability in networks, revealing different supplier engagement in these strategies, which may foster or hinder sustainability diffusion.

The purpose of this paper is to provide the extensive review on dynamic monitoring of forestry area in China.

Countermeasure and suggestions were proposed for three aspects including the establishment of data sets with unified standards, top-level design of monitoring and assessment and analysis models, and establishment of the decision support platform with multiple scenario simulation.

Finally, the authors proposed key research area in this field, i.e., improving the systematic and optimal forest management through integrating and improving the data, models and simulation platforms and coupling the data integration system, assessment system and decision support system.

The authors explored the limitation of dynamic monitoring and state of the art research on data accumulation, professional model development and the analytical platform.

The purpose of this paper is to describe challenges and lessons learned in the design and development of a comprehensive, flexible environmental management system (EMS) in a real university setting; also to inform development of similar systems elsewhere and provide a modular, extensible software architecture for such efforts.

A modular, flexible software architecture was designed as the cornerstone of a comprehensive, secure web‐based data collection and analysis framework. Environmental data such as utility usages, waste generation and transportation services were identified, collected, and entered into the evolving system. The system is easily extensible to new environmental data types, and supported manual and automated data entry, custom “at‐the‐source data entry” mechanisms, and flexible tools for visually analyzing environmental data captured.

Development of automated EMS systems for large institutions is significantly complicated by profound heterogeneity in campus infrastructure, management policies, and limited data accessibility; legacy data are often incomplete or inaccurate. Successful EMS initiatives must explicitly address these challenges through realistic project planning, choice of software technologies, design of system architecture, and administrative commitment. Detailed insights in each of the above areas are provided.

The authors provide clarifying discussion of sustainability plans versus monitoring systems, place popular technological gadgets such as live building energy monitors into perspective within this framework, and describe design and implementation of a comprehensive environmental monitoring framework. The modular concept for system architecture, design approach, and lessons learned can inform the development of similar comprehensive EMS development efforts.