Internet of Things is a form of distributed computing based on networks of devices embedded with sensors and interconnected by internet. Each device contains sensors, actuators, and software to measure physical parameters plus internet connection, with the objective of connecting with other devices and exchanging data – to either mutually help each device to better accomplish its individual task by receiving more physical information or, by accomplishing a combined task together.
INTERNET OF THINGS (I.o.T) DEFINITION
The term first became popular in 1999 in an internal presentation by Kevin Ashton for M.I.T. and Procter & Gamble (1). Its initial use was for RFID tags (Radio Frequency Identification) and it was immediately applied to consumer product uses, in home appliances like smart TVs, in wearable technology, and above all in smart home and domestics – interconnecting appliances like lighting fixtures, thermostats, home security systems and cameras.
IoT is one of the rare cases in which surrounding hype has indeed understated its real full potential. IoT has helped enormously in the previous Digital Revolution by facilitating the digitalisation of the physical world. The innovation capacity of IoT has increased and is currently being integrated with other technologies, such as Robotics, Big Data Analytics and AI. It allows for such a huge of applications, to the point that it is considered one of the pillars of the 4th Industrial revolution.
ENABLERS OF THE PRESENT INDUSTRIAL INTERNET OF THINGS (I.I.o.T.)
Industrial Internet of Things (IIoT) refers to the use of IoT initially in industrial production and by extension to any sector. IIoT focuses on the networking of machines to achieve seamless process chains by leveraging and integrating AI, BigData Analytics and Automation and Robotics technologies including technical advancements in wireless sensors, radio frequency identifications tags (RFID) GPs, and internet protocols and achieving important increase of the effectiveness of companies and operators.
Low Cost Sensors and Actuators
Low cost, miniaturised sensors, actuators, and intelligent devices collect physical and chemical parameters, such as temperature, humidity, amount of light, gases, and data related to predictive maintenance and energy efficiency and they are of general application in monitoring of machines, and installations. An actuator is a device, that in order to automate a process, is capable of transforming energy into an action, like relays to cut off electrical current, indicator lights and solenoid valves. The data collected by sensors and actuators is then sent seamlessly to Cloud servers.
Cloud computing Provides BigData Processing
Provided by CC, without the requirement of fixed capital, the resulting information is used as the base for automated processes. Major cloud providers such as Microsoft, Amazon Web Services, Google, and a myriad of specialised players, now provide IoT platforms, the computing power and the analytics that facilitate the development and administration of IIoT applications.
IIoT Platforms and Applications
The building blocks of an IIoT system are specialised tiered applications, generally located and managed by powerful cloud, based IoT Platforms that collect data from myriad of devices’ sensors and actuators. After analysis, it makes the information available to users, operators and also sends instructions back to the original and new devices. To provide an illustration of the extent of present services provided, there are three tiers of applications: The first tier is Enterprise Operation and Integration applications that monitor the environment, tasks, vehicles, engines engine status etc and integrates the data at enterprise level.
The second layer of applications provide historical analytics based on AI and connection to people, and downstream the information to generate alarms, alerts, rules to conduct processes and changes in those rules.
Additionally, there is a third layer of applications to apply the analysed data to improve the devices and sensors drivers and their management.
IIoT ADOPTION AND EFFECTS
The combination of sensors, powerful on-demand Cloud Computing and IoT Platforms, allow devices to provide optimal functions in, among other areas, smart maintenance, operations management, fleet monitoring, route monitoring, remote area surveillance, and smart warehouse and inventory management. To illustrate the IoT’s economic impact on the improvements in inventory, logistics, and overall supply chain, a global annual savings of €460 to €700 billion is estimated to be reached by 2025. (2)
CETMO Analysis, adapted from McKinsey & Company (3)
As discussed in the AI and Automation and Robotics sections, IoT also presents a broad range of uses and acceptable adoption that is expanding rapidly with key players in manufacturing and logistics. AI is already reaping its benefits. DLH estimates the general adoption and deployment of this technology with a high economic impact will happen within 3-5 years, faster than Robotics and Automation and AI (4) for example. Additionally, IoT component manufacturers and platform and service providers continue to consolidate and expand its offerings. Regarding IoT Platforms, Microsoft, IBM, Oracle, SAP, and Hitachi offer such reliable services.
IIoT EFFECTS ON CORPORATE AND COUNTRY DISPARITY
IIoT has been identified from its inception as a KETTL that generates large benefits, not only for logistics, but also and particularly to all passenger and freight transport sectors. Indeed, the quick advances, falling costs, scalable nature and sufficient adoption taking place, facilitates some kind of adoption, with limited risks, even to small operators, and is already generating a small boon for smart modest adopters.
IIoT has a clear application in developing countries to bypass present limitations in infrastructure. For example, in fleet management and location in transportation, city management, sustainable energy in isolated areas with low-cost use of solar energy, as well as innovative pay-as-you-go transaction models using IoT enabled devices.
RFID Journal, Volume 22, Ashton,Kevin, The Internet of Things, 2009
Mackinsey & Company, The Internet of Things: Mapping the Value Beyond Hype, 2015 link
McKinsey & Company. Ashutosh, Hastings, Murnane, Neuhaus, Automation in Logistics: Big Opportunity, Bigger Uncertainty, 2019. link
DHL, Logistics Trend Radar, 5th Edition, 2020. link
The distributed computing allowed by IoT, with the collection of the myriad of data provided by the sensors and actuators embedded in devices, and their analysis in the Cloud by 3rd part application providers, as well as the instructions sent back to the devices to correct and act, allows for an impressive level of automated efficiency and a broad range of effects. Examples of which are:
Planning quality is significantly increased by having multiple additional inputs. Planning is more precise, detailed, and better adjusted to reality. As a result, the delta between Planning and operation is reduced.
Better control of port operations such as stowage and cargo control. Fuel consumption control and fuel emission reduction. Improving risk detection and prevention.
Goods Location in real time and with complementary information (for example, temperature, humidity, security control, replacement of containers) that permits more effective control of the goods in need of particular treatment.
Uninterrupted Traceability throughout the logistics process, and integration with different agents, including the customer themselves. Traceability of extensive and real-time service performance indicators are automatically processed, resulting in a more accurate picture of the company. Improves understanding of the business, and the
Added Transparency and updating of the organisation’s information towards customers, due to autonomous and automatic collection and delivery of information.
Universal Access: immediate and complete access to planning data.
Near Total Operation Control: including for example infrastructure’s state, location of the fleet, consumption including integration of information from different agents.
Multi-Agent Traceability of commercial procedures, in real time, with indicators accessible from the different agents involved in the processes.
Proceduresand Transaction Traceability such as requests, orders, suggestions, complaints, claims, improving the relationship between all participants (suppliers, operators, users).
Sources: CETMO and “Impacte de les KETs en la digitalització dels diferents àmbits del transport”, CENIT-CINESI – December 2020