Recent reports about the Internet-of-Things (IoT) market suggest that IoT’s business value will be realized in a variety of different sectors including energy, manufacturing, smart cities, healthcare and more. These sectors include both consumer and industrial settings, which gives rise to a broad taxonomy of IoT applications in Consumer IoT (CIoT) and Industrial IoT (IIoT) applications. Market analysts estimate that IIoT is likely to contribute to two-third of the total IoT business value in the coming ten years, which is the reason why IIoT is considered the most important IoT segment. IIoT’s importance stems from its central role in the next wave of industrial applications, which will be based on digital data and services. This evolutionary step in industrial applications is coined digital transformation of industry or even fourth industrial revolution (Industry 4.0). The fourth industrial revolution is reshaping industrial processes in different areas including energy, manufacturing, smart cities, oil & gas and supply chain management. In all these areas there are already use cases with tangible business benefits and a proven Return on Investment (ROI), which are already being implemented in real-life environments such as plants, factories and oil refineries. In this article, we introduce the characteristics of IIoT applications and their close affiliation with Cyber-Physical Systems (CPS), while explaining how CPS systems are enabling Industry 4.0. Accordingly, we present a set of prominent use cases in different industrial sectors, such as manufacturing, energy, oil and gas as well as smart cities. We focus on use cases with proven business value, which are already prioritized for implementation by industrial organizations worldwide. The article ends-up providing a future outlook about IIoT and the evolution of the presented use cases in the coming years.  

Cyber-Physical Systems and Industry 4.0

For several years, the majority of IoT applications focused on the collection and processing of data from numerous heterogeneous sensors and wireless sensor networks (WSN). The primary functionality of these applications was the extraction and visualization of knowledge and information from a variety of sensor sources. To a lesser extent, IoT applications involved actuation and real-time control. Nevertheless, actuation and real-time control are the functionalities that will enable IoT to deliver the lion’s share of its business value in the coming years, as IoT applications will not be limited to knowledge extraction for improved decision making. Rather, they will also provide the means for interacting with field devices and the surrounding physical environment as a means of increasing automation and performing tasks in less laborious and less error prone ways than humans. Such real-time control and actuation capabilities will be empowered by the advent and proliferation of cyber-physical systems.

Cyber-Physical Systems

Cyber-Physical Systems (CPS) can be defined as open, networked systems, which capture and analyze the physical world’s context and accordingly provide a wide range of networked-based services including both data-intensive services that drive business processes and low-level actuating services that control the behavior of devices, objects and services in the physical world.  In essence, CPS system are bridges between the physical and the cyber worlds i.e. between field implementations and IT systems. Some prominent examples of CPS systems are:
  • An Intelligent Workbench, which flexibly adapts its height to the physical characteristics of its human operator. The latter can be read and communicated to the CPS system via a RFID (Radio Frequency Identification) tag that contains the identifier of the operator.
  • A Smart Machine, which provides information about its operative condition and status, based on a variety of embedded sensors, such as vibration, temperature, acoustic and ultrasonic sensors. In this case, the embedded sensors provide to digital systems detailed and accurate information about the status of the physical device.
  • An Industrial Robot, which completes warehouse or production tasks in a plant, while at the same time providing data about its location and the status of its activities to an IT system. Such a robot can be used to drive the automated configuration of production tasks (e.g., which parts to be assembled, what type of parts to be used in the assembly process) based on digital data that could be given as input to its controlling IT system.
Beyond such basic CPS devices, it is possible to interconnect and federate multiple networked CPSs into large-scale systems, based on a System-of-Systems (SOS) approach. For example, the marine infrastructure of an entire port can be considered as a large scale CPS system, since it comprises a range of federated and closely interacting IT and physical systems. IoT involves the integration of the physical and the digital worlds, which allows one to consider an IoT system as a CPS system. In several countries and applications domains (e.g., manufacturing) the term CPS is preferred over IoT or Industrial IoT, yet both terms denote more or less similar systems and functionalities. However, IoT is a more widespread term, given the broader awareness about it. CPS systems tend to be used in the scope of IoT deployments that comprise real-time actuation and control.

The Digitization of Industry

CPS systems already play a significant role in the development and operation of many innovative services in different sectors, including smart manufacturing, ambient assisted living, connected cars and more. Furthermore, a significant increase and evolution of CPS deployments is anticipated as a result of exponential increases in processing power, data capture, data transmission and data storage capacity. CPS systems are associated with some of the most disruptive technology revolutions of our time, including the fourth industrial revolution. Indeed, based on their ability to integrate the physical and the digital worlds, CPS systems serve as a basis for the integration of Operational Technology (OT) with Information Technology (IT). The convergence of OT and IT is fundamental for the digitization of industrial processes, which are in most cases based on conventional OT such as machines, tools, PLC (Programmable Logic Controllers), SCADA (Supervisory Control and Data Acquisition) systems, sensors and other field devices that are ubiquitous in industrial plants. As part of the digitization of industry, all these devices become interconnected based on IoT networks and infrastructures, which enable them to exchange information seamlessly both with the plant and across the supply chain.  In this way, plants are able to drive their processes based on timely and accurate information about connected processes such as machine failures, delays in shipments, placement of critical orders in the supply chain, the status of workers and more. Overall, Industry 4.0 is about integrating CPS systems in industrial plants and using them to drive and carry out industrial processes. Based on CPS systems these processes can be informed, intelligent, more automated and less error prone. Industry 4.0 has been originally perceived as a paradigm shift in the manufacturing sector, where CPS-based manufacturing has been branded based on the German term “Industrie 4.0”. However, the concept of the fourth industrial revolution and of the digitization of industry has been extended to other sectors as well.

Industrial IoT Sectors and Use Cases

The following IIoT and CPS system use cases are in five different sectors, which are already under transformation as part of the digitization of industry. We focus on use cases with a highest value, yet our list is not exhaustive.


The digitization of manufacturing affects two main classes of industrial processes: (i) Processes within the factory, which aim at increasing automation, flexibility and production quality at a lower cost; (ii) Processes associated with the manufacturing chain, which create connected and intelligent supply chains that are able to automatically adapt and optimize themselves based on triggers from the environment. Along these two axes, the following prominent use cases are deployed:
  • Predictive maintenance: This involves the transition from conventional (suboptimal) preventive maintenance processes to (superior) predictive maintenance for factory assets and equipment. Predictive maintenance is based on the collection and analysis of large sensor data sets about the status and condition of the equipment, including vibration, temperature, power consumption, thermal images, acoustic, ultrasonic and other type of digital data. Upon the extraction of a credible end-of-life (EoL) estimate about the equipment, predictive maintenance applications can combine it with data from the business information systems (e.g., such as ERP -Enterprise Resource Planning) in order to calculate the optimal maintenance schedule, which minimizes down times and maximizes OEE (Overall Equipment Efficiency).
  • Flexible automation: Nowadays, manufacturers have no easy to deploy new automation technologies in the shop-floor, such as for example smart sensors, RFID tags and 3D printers. Indeed, such changes require tedious re-engineering and reconfiguration processes for both OT and IT systems. Based on the digitization of industry, the configuration of factory automation systems can be done at the digital layer without any need to deal with the low-level details of OT. This provide flexibility in automation, which reduces costs and enables manufacturers to benefit from the latest automation technologies.
  • Quality control and zero defect manufacturing: Industry4.0 opens new horizons in the quality control of industrial processes, through enabling collection of vast amounts of data from production lines, along with their combination with quality-related information in business information systems (such as ERP and MRP – Manufacturing Resource Planning – systems).  This information can be then analyzed in order to spot quality problems in real-time, while at the same time planning for zero-defect processes.
  • Factory simulation: CPS systems enable the acquisition and processing of large amounts of digital data from shop-floor devices and processes. These data enable the simulation of the plant, at multiple levels from the level of individual devices to the entire plants. In this way, what-if scenarios about changes in automation, alternative option for maintenance, production scheduling processes and more can be executed and evaluated prior to their ultimate deployment on the field.
  • Manufacturing chain collaboration: The interconnection of different CPS systems and business information systems across the manufacturing chain enables the seamless flow of timely and accurate information across all involved stakeholders. This can reduce supply chain costs, facilitate stakeholders’ collaboration in product development, while at the same time enabling accurate forecasts about the supply chain operations.


Smart networks and IIoT devices are transforming the energy sector, through enabling grid optimizations, real-time balancing of supply and demand, as well as more active engagement of users. The collection and processing of data from smart networks facilitates also the creation and management of data-driven portfolios of services. Relevant use cases include:
  • Supply and Demand Balancing: IIoT enables the deployment of smart meters that provide real-time information on energy usage and consumption. Based on information about energy usage in different locations and across various time scales, ESCO (Energy Service Companies) are able to dynamically balance supply and demand, taking into account the available resources and providing relevant (dynamic) pricing incentives to both producers and consumers.
  • Consumer and Prosumer Engagement: The advent of IIoT technologies empowers new forms of consumer engagement, where consumers participate in optimized energy consumption in exchange of monetary benefits or other incentives. This includes scenarios where consumers participate in the energy production process i.e. they become “prosumers”.  Typical examples include electromobility and Vehicle-to-Grid (V2G) scenarios, where (renewable) energy stored in the battery of the electric vehicle is used as an energy provider in prosumer scenario. Another example, involves the engagement of consumers in energy savings as part of in-home scenarios, which can be based on gamification schemes.
  • Aggregator based business models: IIoT is disrupting the energy market through the introduction of new business models. Such business models involve a new business actor, namely the energy aggregation company, which undertakes to negotiate on behalf of multiple prosumers, each one having a small individual negotiating power. New business models are also empowered by the integration of blockchain technology in IIoT, which provides the means for specifying and enforcing smart contracts between different stakeholders of the energy market.
  • Microgrid generation and renewables sources (RES): The energy sector is characterized by an increased deployment of micro-grid energy systems such as Solar PV and other renewable distributed generation (DG) technologies. IIoT technologies facilitate the collection and combination of micro-grid data from diverse technologies such as Combined Heat and Power (CHP), solar PV, and lithium ion energy storage.

Oil and Gas

Oil and gas operations involve a wide range of industrial processes, including crude oil extraction, oil refinement, oil pumping, as well as oil gas and water separation and storage. IIoT enables the deployment of a wide range of sensors and CPS systems, which facilitate applications that provide real-time insights about the process, along with support to mechanical and electrical processing activities. Relevant use cases include:
  • Real-time process monitoring and visibility: The deployment of multiple sensors across all the stages of the oil and gas processes facilitate real-time visibility of the process, including information about the what, where, when, why and how of the extraction and processing activities.
  • Employee activities tracking and safety: Employees can be equipped with wearable devices in order to track their performance and safety. Moreover, the wearables devices could be able to display advanced cyber-representations of the oil refinery (such as Augmented Reality) in order to facilitate the workers to perform their tasks.
  • Quality control: Based on sensors, RFID tags and other devices, IIoT applications can be used to monitor and certify oil processing activities and their conditions such as pushing of the oil in pipelines, changes in evaluation, pressure decreasing factors, storage levels and more. In this way, timely and accurate quality control processes can be established.

Public Infrastructure and Smart Cities

IIoT is one of the main enablers of sustainable applications in smart cities, which propel the city’s economic growth and improve the quality of life for the citizens. A variety of IIoT use cases can be implemented on public infrastructure comprising broadband networks, lighting, smart water pumps, traffic sensors and more. Representative use cases follow:
  • Smart Transport and Urban Mobility: Moving between two points in the city is probably the most common problem in modern urban environments. In order to confront this problem, IIoT enables transport optimization across various levels and timescales, including real-time timescales (e.g., traffic rerouting) and planning timescale (e.g., urban planning, trip planning).
  • Smart water management: IIoT technologies provide both utility companies and consumers with the means of monitoring water consumption and the status of the water infrastructure. Moreover, they also enable rapid actuation in the case of problems (e.g., leakages) including cease of operations in selected parts of the affected network.
  • Urban safety: Recent terror incidents in major European and U.S cities have revealed the security and safety vulnerabilities of urban environments. IIoT technologies facilitate the collection and processing of information from a wide range of sensors and CPS systems, including cameras, motion trackers and drones. This information can be processed in order to proactively undertake preventive measures, but also in order to appropriately deploy resources (humans, equipment) in proper places as part of coherent and well-planned security missions.
  • Smart Buildings: IIoT enables intelligent buildings [10] that optimize their use of natural resources (e.g., energy, water), ensure maximum comfort for their inhabitants and enable applications such as facility management.
  • Applications interoperability: Following the deployment of multiple fragmented projects (i.e. “silo” deployments) smart cities are seeking ways for integrating data and services from different deployments in an interoperable way. This facilitates the monitoring and tracking of city-wide performance indicators, based on multiple rather than a single IoT deployment. Moreover, they facilitate strategic planning about how to reach ambitions performance targets, based on the configuration of the operations of various projects in the city.

Conclusion and Future Outlook

IIoT represents the portion of IoT with the highest business value. Using CPS systems, plant operators and supply chain participants are capable of deploying disruptive innovations in wide array of sectors, including manufacturing, energy, oil and gas, as well as smart cities.  Early use cases have validated IIoT’s potential in these sectors. On-going advances in the IIoT space such as the rise of smart objects (e.g., drones, robots, smart wearables) and the emergence of the blockchain technology will broaden the spectrum of possible use cases, while at the same time increasing their security, scalability and reliability. Nevertheless, there are still several technical and business challenges to be confronted prior to IIoT becoming mainstream in industrial plants and oil refineries. At the technical forefront, there is a need for ensuring the security and scalability of the IIoT deployments, given the mission critical nature of industrial processes, but also the fact that they typically entail thousands of different systems and devices. Furthermore, some of the underlying technologies (e.g., the blockchain) are in their infancy and the need to mature prior to becoming an integral part of the plants. At the business forefront, there is still a need to identify successful business models for some of the presented use cases. Moreover, plant owners are deeply concerned about the migration of their existing systems and processes to the Industry 4.0 paradigm, since they need to be convinced that they get the benefits at the lowest possible risk. On top of these technical and business concerns, there is also a prominent talent gap in IIoT technologies such as CPS systems, industrial robots, BigData, blockchain systems and more, which is another set-back against the rapid deployment of the IIoT paradigm. However, the IIoT paradigm to industrial operations is here to stage, as numerous industrial organizations worldwide are already leveraging early benefits, while grasping the future potential of the fourth industrial revolution.