# Production Plant and Warehouse Automation with IoT and Industry 5.0
## 4 Observations and Derivations
### Implementation Analysis  
This paper sheds light on the temperature monitoring system, and other different parameters to review the gas, oil, chemicals, and other manufacturing industries. The research is limited to the different parameters to be used based on technical comparisons;therefore, no specific implementation analysis can be entitled. This paper also presents the key components of IIoT architecture, which include devices, such as sensors, interpreters, the transient data store, which temporarily stores transient data objects to avoid data loss, and local processors serving as low latency data processing systems [45]. Application is a presentation layer that helps staff to understand things interactively. Channels are a medium to exchange data; they include IP routers, switches, and other networking protocols. Gateways are used to ensure a connection with other networks. Collectors provide help to collect data from different gateways [46]. Processors are used to transform data, detect various signals, and other complex event processing. Permanent data store provides storage, such as cloud storage, RDBMS, data repositories, open-source data, and website data. The models in IIoT comprised of analytical models and data models. These analytical models are trained using artificial intelligence. Security includes encryption, authentication, and firewalls [47]. Computing environments differ from enterprise to enterprise. Fog computing is used for analytics purposes. Cloud computing is used to scale things globally. Hybrid computing is a mixture of fog and cloud computing.  
This paper discusses a conceptual-based implementation of IIoT by dividing them into three layers: the sensor layer, communication layer, and presentation layer. This paper also discusses the big data applications in IIoT [53]. This article proposes an EMS based on the IoT (IoT) network that boosts power quality for smart factories to establish an energy-efficient system. In addition, the architecture for improving the power quality in industries that follow ISO 50001 standards is suggested. Before implementing IoT in warehouses and production plants, there are some key requirements, such as domain requirement knowledge; IT office in industry; good quality hardware; large scale or big data handling; real-time monitoring; interoperability with other software or interfaces; the scalability of IoT devices to expand the business; and the reliability of device functionality [31]. The bandwidth of the network is also a great problem to transmit the data in real-time, such as NBIoT devices.  
Implementing IoT in industrial sectors requires the consideration of various aspects to elicit the requirements. It includes the identification of the particular industrial sector, understanding of the business requirements of that particular industrial area, infrastructure requirements, addressing integrating issues in case of the up-gradation of the existing IoT system, and an understanding of human and social aspects in the case that training would be required for the people who are expected to interact with the system [38]. Depending upon the requirements, a threshold needs to be set for the quality factors of the system as well as leaving provisions in the systems for integrating functionalities and capabilities that can be required to be added in the future.