**6. Case studies of IoT-enabled energy management**

Several case studies have examined the implementation of IoT-enabled energy management in various industries. The following are examples of such case studies:

#### **6.1 Smart homes**

A systematic study investigated the impact of smart home technology on energy consumption. The study utilized IoT-enabled devices such as smart thermostats, smart lighting, and smart appliances. The devices were connected to a central hub, providing real-time energy consumption data. The results showed a significant reduction in energy consumption by 10–15%, resulting in cost savings for homeowners [17]. However, the study also highlighted the need for data security and privacy measures to be implemented, as the devices collected sensitive information such as occupancy patterns. The study by Alenazi et al. proposes an energy-efficient neural network embedding technique in IoT over passive optical networks to enhance the performance of IoT-based applications while reducing energy consumption [18].

#### **6.2 Cloud distribution**

In addition to using AI and IoT to reduce energy consumption, the work by Alenazi et al. also proposes the concept of cloud distribution to enhance energy efficiency in IoT-based applications further. The cloud distribution approach involves distributing the processing load of an IoT application across multiple virtual machines in the cloud. This allows the load to be balanced across multiple machines, reducing the energy consumption of each machine and increasing overall efficiency [19]. The study evaluates the energy efficiency of this approach in comparison to traditional approaches and demonstrates its effectiveness in reducing energy consumption [19]. With the increasing demand for IoT-based services and the associated energy consumption, the proposed approach can significantly benefit both the environment and the economic sustainability of IoT-based applications.

#### **6.3 Manufacturing**

In another study, IoT-enabled sensors were installed in a manufacturing plant to monitor energy consumption. The sensors were placed on equipment such as motors, compressors, and conveyors and provided real-time data on energy usage [20]. The data were analyzed using machine learning algorithms, which identified areas for optimization. Implementing IoT-enabled energy management significantly reduced energy consumption annually. However, the study also highlighted the need for interoperability among different IoT systems, as the sensors used in the study were from different manufacturers, and it was challenging to integrate the data from these sensors.

#### **6.4 Transportation**

The California Department of Transportation (Caltrans) implemented an IoTenabled energy management system in its highway lighting systems [21]. The system utilized sensors and smart lighting technology to monitor and control lighting usage. The sensors on the light poles provided real-time energy consumption data. The system was also integrated with weather data, which enabled the lighting to be adjusted based on ambient light levels. Implementing the system resulted in a reduction in energy consumption and a significant reduction in maintenance costs [21]. However, the study also highlighted the need for data security measures, as the system collected sensitive information such as traffic patterns and vehicle speeds.

In these case studies, IoT-enabled energy management systems provided significant benefits, such as improved efficiency, cost savings, and better resource utilization. However, implementing these systems posed several challenges, including data security risks, interoperability issues, and privacy concerns. For example, in the case of the smart home study, concerns were raised regarding the security and privacy of the data collected by the IoT-enabled devices. Therefore, it is crucial to address these challenges to realize the potential benefits of IoT-enabled energy management systems.

**Figure 8** illustrates a visual representation of diverse applications of the Internet of Things (IoT). These applications encompass various sectors, showcasing IoT's wide-ranging impact. The figure depicts IoT's transformative influence on sectors such as smart homes, agriculture, healthcare, manufacturing, transportation, and energy management. In smart homes, IoT-enabled devices, including thermostats,

**Figure 8.** *IoT applications [4].*

#### *IoT and Energy DOI: http://dx.doi.org/10.5772/intechopen.113173*

lighting, and appliances, connect and exchange data to optimize energy consumption and enhance convenience. In agriculture, sensors integrated into fields and livestock enable real-time monitoring of conditions, facilitating precision farming and resource optimization. In healthcare, IoT devices collect patient data, enable remote monitoring, and enhance medical diagnostics and treatment. In manufacturing, IoT-driven monitoring and automation optimize production processes and equipment maintenance. In transportation, connected vehicles and smart traffic systems improve traffic flow, reduce congestion, and enhance driver safety. Importantly, the figure highlights the specific application of IoT in energy management, demonstrating its potential to revolutionize the efficient use of energy resources across sectors.

IoT's transformative potential extends beyond energy management into telecommunications and cloud computing. Ericsson's research suggests potential energy savings of up to 40% through IoT-enabled energy management in telecommunications networks. Moreover, Google's integration of AI and IoT in data center energy management achieved a commendable 15% reduction in energy consumption. Cisco's projection of IoT devices connected to 5G networks yielding up to 90% energy consumption reduction underscores IoT's cross-industry energy efficiency potential.
