Green IoT (G-IoT) Ecosystem for Smart Cities

We are in the era of Industry 4.0 with the world going towards everything, everywhere, and anytime with “things” being enablers of technology. Our world is becoming smarter with everything (mobile phones, cars, TVs) connected to each, having unique addresses and communication mechanisms. It is foreseen that by 2025 every little thing, like pen, paper, food packages, etc., would be operated over the internet by internet of things (IoT) towards a smarter world. However, in order to enable the smart world to be sustainable, IoT should be embarking into energy efficient (green) paradigms. Since IoT is also a key enabler for smart cities, a green-aware design of smart cities could see a potential to create a green IoT ecosystem for smart cities. This ecosystem would comprise the green IoT lifecycle, the six pillars of smart cities, and focusing on the green infrastructure, green applications, and green energy. This conceptual study would motivate researchers embarking into smart city projects and keeping green concepts intact in their design and implementations.

Incentive-Based Scheduling for Green Computational Grid

In the computing grid environment, jobs scheduling is fundamentally the process of allocating computing jobs with choices relevant to the available resources. As the scale of grid computing system grows in size over time, exponential increase in energy consumption is foreseen. As such, large data centers (DC) are embarking on green computing initiatives to address the IT operations impact on the environment. The main component within a computing system consuming the most electricity and generating the most heat is the microprocessor. The heat generated by these high-performance microprocessors is emitting high CO2 footprint. Therefore, jobs scheduling with thermal considerations (thermal-aware) to the microprocessors is important in DC grid operations. An approach for jobs scheduling is proposed in this chapter for reducing electricity usage (green computing) in DC grid. This approach is the outcome of the R&D works based on the DC grid environment in Universiti Teknologi PETRONAS, Malaysia.

Composite Identity of Things (CIDoT) on Permissioned Blockchain Network for Identity Management of IoT Devices

Internet of things (IoT) is in the forefront of many existing smart applications, including autonomous systems and green technology. IoT devices have been commonly used in the monitoring of energy efficiency and process automation. As the application spreads across different kinds of applications and technology, a large number of IoT devices need to be managed and configured, as they are capable of generating massive amount of sensory data. Looking from this perspective, there is a need for a proper mechanism to identify each IoT devices within the system and their respective applications. Participation of these IoT devices in complex systems requires a tamper-proof identity to be generated and stored for the purpose of device identification and verification. This chapter presents a comprehensive approach on identity management of IoT devices using a composite identity of things (CIDoT) with permissioned blockchain implementation. The proposed approach described in this chapter takes into account both physical and logical domains in generating the composite identity.

Challenges and Issues of IoT Application in Heating Ventilating Air Conditioning Systems

The internet of things (IoT) is a system consisting of computing, mechanical, and electronic devices, which are having ability to transfer data in network without human interaction. The sensors used in IoT collect and transfer the data to the cloud, which is further processed using software to perform an action. The IoT is one of the fastest growing industries, and in recent years, it is most widely used in HVAC systems in residential and commercial applications to reduce the energy consumption as building consumes by approximately 40% of total energy. The IoT reduces the energy consumption of the building by optimizing the process variables of HVAC system components, increases life of system components, enhances the comfort of the occupants, and provides remote control of the system. However, there are challenges in data security and privacy, and also there is a lack of IoT platforms specifically oriented towards the proper processing, management, and analysis of such large and diverse data.

Green Energy in Data Centers Using Internet of Things

Green energy infrastructure with the internet technologies relies on five important domains: green machine to machine (M2M), green cloud computing (CC), green data center (DC), green ICT, and green cellular. The ever-increasing demand for cloud computing and heavy dependence on cloud for storage, processing, and applications results in the need for more data centers with high capacity. Power management using wireless sensor networks (WSN) can be a potential solution as there has been a lot of works suing WSN for power management for green buildings, green home, and green farming. The same design can be applied to data centers with modifications to cater for data centers. Since WSN is part of IoT, various IoT-related solutions can be proposed for green data center solutions. A hybrid model that consists of virtualization, cooling systems, and IoT shows energy efficient data center designs. There have been various efforts as such, and this research will present green energy designs and mainly IoT-related initiatives for green-aware data centers.

Green Energy Harvesting and Energy-Efficient Routing Protocol in Internet of Underwater Things

The ability to sustain communication between nodes as per Industry 4.0 standard within the waterways is still not mature enough. It is prudent to make use of natural resources that are abundantly found in the form of strong wind (wind energy) and underwater tidal waves generation (tidal energy). Climate change and environmental sustainability are now becoming more important for a sustainable smart world. This is discussed in detail along with the decentralized mode of crop management. In this chapter, it is shown that energy efficiency can lead to the selection of different system models for the internet of underwater things (IoUT) where systems are sustainable and can tap previously unexplored resources. This resource is useful as a reference to further explore IoUT and green energy harvesting techniques.

Internet of Things for Green Building Management

The expansion and development of advanced technology by mankind have a great substantial impact on the natural environment. The buildings consume a large number of natural resources during their construction, design, and operation process. Due to the manipulation of natural resources by the buildings on a large scale, there is a need of better-designed buildings for effective and efficient use of resources. The concept of “green buildings” is an innovative solution for the aforementioned issues and promotes eco-friendly activities. Internet of things (IoT) transforms the idea of green building into real. Considering a large number of IoT applications, the objective of this chapter is to survey the major IoT concepts for green building management. The survey is conducted by summarizing a large number of scientific contributions to the field (i.e., internet of things for green buildings) and presented in this study. This chapter also describes the open research challenges for future work in this emergent area.

IoT Underwater Wireless Sensor Network Monitoring

Water is a crucial resource for all life on earth, and it is fast becoming one of the limited natural resources to humankind, especially clean drinking water and water for agricultural uses. Sensor technologies and wireless communications (both terrestrial and underwater) have been seriously investigated by researchers to find ways to integrate these technologies for a novel data-sensing and data-collecting network for long-term water pollution monitoring purposes. This chapter describes an IoT-based underwater wireless sensor network (UWSN) which is believed to have a huge potential for monitoring the health of river, lake, reservoir, and marine environment. The sensed data from IoT sensors are communicated wirelessly via acoustic channels to a data collection center for further processing and interpretation. It is foreseeing that judicious deployment of IoT-based UWSN is a promising solution for long-term water quality surveillance.

Energy Harvesting Models and Techniques for Green IoT

Wireless sensor networks (WSNs) have been popular due to their wide range of applications in almost all walks of life including industry controls, environmental monitoring, health, transportation, military. Usually conventional sensor networks are dedicated, and private networks have little or no communication with the outside world; hence, when connected to the external world by using internet protocol (IP), they form a network of connected devices, sensors, and systems and form an internet of things (IoT). Due to rapid development of IoT infrastructures worldwide, energy demand has been increased significantly to meet the power requirements of billions of connected devices. Since WSN is a foundation of IoT; hence, IoT also inherited with the challenge of providing consistent energy and to maintain hazard-free environments. This chapter is the extension of “Energy Harvesting Models and Techniques: A Review,” which focuses on possible energy sources available in ambient environment and the technological mechanism to harvest energy for WSN and IoT that promotes green energy concept.

Globally Renewable Energy Consumption Sources

Electricity consumption will be part of a large conversation about connected with international electricity demand in the next two decades. Renewable energy sources and climate change modify minimization and offer a good estimation for the technological, scientific, environmentally friendly, financial, and also societal aspects. This research is the extended version of the research presented in IGI global book Role of IoT in Green Energy Systems, 2015. A full assessment related to any profile minimization options will likely involve an evaluation of respective potential alongside minimization with the bargain with sustainable development as well as all associated risks and costs.