## 3 Internet of Things in Industrial Applications
### Recapitulation of Contemporary Research Developments in the IIoT  
The privileges of wireless sensor network (WSN) technology as earlier-mentioned find rewarding applications in the industries in what is termed IIoT. The numerous benefits of this technology can be exploited in a considerable number of industries such as the fire industry, manufacturing, power generation and transmission industry, security systems etc. Some neoteric findings were made for use of WSN in IIoT and are discussed as follows. An update of research trends and challenges in the fire industry are summarized as reported in [42]. A SoA for fire IoT consisting of four layers namely _sensing layer_, _network layer_, _service layer_ and _interface layer_ is also presented in this paper. The importance of IoT in the fire industry cannot be overemphasized as fire security technologies offer warning information to industry owners, security agencies such as police and fire brigade services as well as other emergency management services for the safeguarding of lives and industrial properties. The timely fire information provided by the IIoT technologies can be used to alert occupants/workers to minimize the occurrence of injury, destruction of properties and possible death that may arise from fire emergencies. The fire IoT is designed to integrate several devices which are equipped with identification, sensing, processing, communication and networking devices for the minimization of fire disaster in the industry. Furthermore, IoT technology can be employed in the industries for check-mating the disastrous effects of fire explosions through the fusion of correlated sensor measurements. This IoT-based fire detection technique is achieved by fusing sensor data connected between nodes. As such, a data fusion fire detection method consisting of the fusion of temperature and relative humidity smart nodes is proposed in [43], where the correlation of both temperature and relative humidity sensors are resolved using copular theory. The performance of the proposed sensor fusion-based scheme is compared with existing techniques such as conditional independence sensor scheme and bivariate Gaussian method as proposed in [55]. Results obtained demonstrated that the copula-based detection scheme enhances the performance of local detection across nodes in a significant manner in comparison with the compared schemes. Interested readers are referred to [43; 56; 57] for further reading on copula functions. In [40], the concept of IoT is adopted for environmental monitoring under the aid of robotics where the robots are designed to move autonomously while interacting with the environment. A good example of an IoT-aided robotic system is a _self-driving car_[58]. In this paper, an experimental test bed is developed consisting of an IoT device that is connected to an UAV (commonly known as _drone_) which executes a monitoring mission around a specified area with an IoT network for the exploration of environmental data. In general, robotic networks consist of many robots working together in a collaborative manner, where the robots are equipped with sensing, computing and communication devices in order to enhance the exchange of information over a communication network so that a particular task can be effectively accomplished. Results obtained from this paper [40] (which can be developed further in larger-scale environment) shows that onboard of IoT equipment to the UAV does not incur significant overhead while the overall QoS expressed in terms of data retrieval delay, network joining time and packet loss ratio satisfies the requirements of this experiment. In industrial wireless applications, a robust _time synchronization scheme_ is required for efficient exchange of information and data processing. The synchronization schemes are necessary to enhance the collaborative coordination of the wireless sensor nodes in order to accomplish some useful task for the industrial environment.