Growth in the IIoT market is predicted to exceed $123 billion by the end of 2021.
The Industrial Internet of Things (IIoT) has become an integral part of our growing society. In industrial sectors, a culture of innovation and adapting to meet the future is fueled by on-going IoT advancements.
Industrial IoT has gained its well-deserved reputation by aiding in the development, introduction, and further adoption of modern connectivity and networking facilities in nearly all types of industries – but most notably in the farming, manufacturing, mining, and energy sectors. IIoT has been one of the keys to bringing the traditional industries into line with today’s modern business landscape.
Growth in the IIoT market is predicted to exceed $123 billion by the end of 2021. This projected growth is proof of how industrial IoT has enhanced processes in nearly every single business sector, and how it has been instrumental in delivering services during the height of the Covid-19 pandemic. What’s more, all aspects of today’s tech-dependent society can be further enhanced by emerging IoT solutions.
The widespread adoption of IIoT tech – as well as the continual development seen in the sector – can be attributed to a number of major technologies that act as ‘enablers’ to the growing number of IIoT innovations.
The top five of IIoT solutions enablers right now are:
The main idea of industrial IoT technology is to connect the organic and inorganic elements of the industrial sector together. Physical machines and hardware have been given a new purpose through the use of cyber-physical systems. Existing industrial machines and hardware were connected to networks and systems using IoT technology, and as a result they became accessible to their owners remotely and could be used without the need for physical human intervention.
When network connectivity is added to any physical system, it creates vast possibilities in the form of additional or improved functionality, and the gathering of invaluable data insights. CPS integrates physical processes with software, which allows people to create new IIoT solutions with the goal of making processes more efficient and transparent.
The development of the internet eventually introduced the storage and exchange of data through cloud-based systems. Cloud computing was created as an answer to storage and data access challenges, and to address the issues around devices being susceptible to theft, damage, or catastrophic loss of data due to physical damage or malfunction. Cloud-based services have become a critical part of business operations, and are currently being used by a staggering 94% of enterprises world-wide. IT services have done a remarkable job in this respect by providing a secure method for sending and receiving data over the internet, and making it accessible to machines and humans through reliable and secure connectivity.
Cloud computing has enabled industrial IoT to maintain, monitor, and improve business critical tasks – and do so on a much larger scale than your traditional office-based IoT solutions. The data from within an industry is kept safe and exclusive to its owners, and this pushes enterprises to stay in the forefront of innovation. Data coming from different countries (when international industries communicate) is also shared and received without any much delay and interference. The data being stored and sent is no longer governed by an on-site server – rather, a direct connection to the Internet helps enterprises locate and manage their data without having the need for complex physical networking solutions within their sites.
In contrast to cloud computing (where data is sent to a server to be processed), edge computing brings your data processing facilities to a location much closer to the source of that data. The main concept behind edge computing is decentralized data processing. Following this protocol, all the decision making, data procedures, and notifications are processed much closer to the source of the initial data – shortening response times and removing potential delays in data transfer. Industrial IoT often combines both edge computing and cloud computing. This can enhance the industry’s productivity and services globally, as the speed of processing data is always prioritized and the amount of data transfers lessened.
Industrial IoT is not a small scale operation. Big data analytics promoted the movement and communication of data from various industries on a larger scale. This meant enterprises could decipher and utilize massive amounts of data in a shorter amount of time. Big data analytics within IIoT also meant that companies had access to digitized records, which brought in value in trends and information dating back decades. This linked major industries from all around the world and also created opportunities for industries to work together on common projects and towards common goals.
The idea of a machine that works and processes information like a human has been floating around for decades. Today, intelligent robotics is reshaping industries and is a major reason why the world is developing at high speed. Initially, robots were created to do the ‘heavy-lifting’ and were reliant on a person to intervene in specific processes. Today’s IIoT robots are enhanced with artificial intelligence allowing these machines to make programmed decisions based on certain outcomes within their processes. Machine learning allows for processes to be improved as systems learn to deal with potential outcomes based on previous results. Machine learning has also been incorporated into industrial IoT, so now a machine can evaluate a situation and respond to it – or predict an outcome – without having to be manually programmed to address these situations. Because of these needs, machine learning and artificial intelligence are indeed becoming a crucial part of smart enterprises.
IIoT systems are constructed in an ‘architecture’, made up of ‘layers’, which are built up to form a distinctive modular service infrastructure. The various IoT layers are as follows:
The device layer corresponds to the physical elements of the industrial IoT systems. This layer is made up of sensors, CPS, machines, and other physical hardware.
This layer creates a network that consists of buses, communication lines, and cloud computing protocols. In this layer, data is collected, assessed, and forwarded to the next layer for decoding.
In this layer, collected data is subjected to a series of events that analyze and interpret it. There are specialized applications to fulfill this function and to manage all the data collected. All the information gathered, is organized and combined so that it can be displayed as an output in a logical way.
As the name may indicate, the content layer is responsible for displaying and interacting with the user through a user interface. This is the top-most layer of the whole IIoT stack, and the layer at which end-users are able to see data in a way that is designed for them.
IIoT applications are linking major industrial powers all over the world. Because of this link benefits are seen by both enterprises and consumers alike. Customer-focused practices result in a better customer experience, which then creates transparency and trust between industries and users.
Cross-industry use is by far the main and the most important use case of industrial IoT. The combined efforts of different industries to deliver improvements to basic human necessities is the basic principle upon which cross-industry data sharing is built. All kinds of industrial operations can be made a part of these cross-industry processes – sending and receiving data and in the process, revolutionizing the operations and systems of both today and tomorrow.
One major example of cross-industry IoT is the merging of IT (Information Technology) and OT (Operational Technology). This requires large scale co-operation between vendors, industrialists, and IT experts – however, businesses know that there are real positive outcomes to be had with cross-industry IoT solutions, and they are willing to combine ideas and create opportunities for such things to take place. Once industries achieve their customer-focus targets through cross-industry IoT innovations, the improvements seen in industrial efficiency will speak for themselves .
The initial driving force behind industrial IoT was a simple desire to make already-existing technology work in larger and more complex processes, in an effort to address the challenges faced within industrial sectors. The adoption of industrial IoT proved to be a worthwhile investment of time and effort, and now IIoT is transforming the industrial world – as well as how its core service providers work.
Decades of effort – combined with the industrial goals of making processes less strenuous and more efficient – have brought about the world-wide adoption of IIoT applications, artificial intelligence, robotics, and machine learning.
As industries know all too well, working smart is always better than working hard. Long work hours, the mental and physical strain placed upon people working in remote and high-risk environments, and the high cost of certain industrial operations have led business owners to ask how they can make processes safer and more efficient with today’s technologies.
The advances seen in industrial robotics, AI, and machine learning have created what is now known as Smart Industry. Smart Industry integrates industrial IoT into its solutions, as processes are built and rebuilt around the ideals of increased efficiency and productivity, and lower running costs.
Industrial IoT powers most manufacturing enterprises that want to both produce large quantities of their end product, and keep a close eye on the quality of what they produce. Maintaining the right balance at the industrial level is a crucial step in ensuring that products meet both quality standards and production goals, and this balance can be achieved and maintained with the help of IIoT solutions. The performance of the whole operation is managed and transparent – giving the manufacturer access to key insights and the power to address problems before they arise.
When goods are manufactured intelligently, minimal errors are encountered, and a higher quality product goes to market. All this happens through the maintenance of balance within the manufacturing process, and with more control over operations.
Automation was a controversial topic until the advent of industrial IoT, which debunked many myths and false beliefs about the automation of manufacturing processes. For one thing, reducing manual labor does not necessarily mean replacing it. Automation is often applied to specific points in the production process, where its existence both increases productivity and reduces costs. Automation provides industrial IoT with more opportunities to introduce, implement, and revolutionize industrial systems.
Automation has been instrumental in enabling digital transformations. The applications first seen in industrial IoT are now demanded by the business, logistics, marketing, and construction sectors, and more besides. Automation is making workplaces, homes, and educational institutions more efficient. Machines are now designed to reduce errors within repetitive and labor-intensive tasks that would usually need full-time attention from a group of people.
Industrial IoT in the manufacturing and assembly of automobiles has given the industry a much-needed transparency inside its supply chain. Predicting bottlenecks and issues within the automotive supply chain is crucial to hitting assembly and market targets. Using smart software, all elements and details within the vehicle production process can be digitized and remotely accessed by stakeholders across the enterprise. Automobile manufacturing plants in different countries can communicate efficiently and provide real-time data to headquarters. This bridging of communication gaps helps to increase transparency in industrial processes, and industrial IoT has also been a major helping hand in the import and export of vehicles around the globe.
With the growth of industrial IoT, oil and gas industries have changed their traditional ways and moved on to faster and more convenient options. Oil sensors and related devices are now able to convey the raw data they collect through to base stations for storage and analysis, without having to worry about distances and connectivity interruptions.
With advancements in industrial IoT, oil and gas industries are now working with minimal environmental impacts when producing their products. Along with that, security is better than ever, pricing fluctuations are managed in correspondence to other suppliers, and maintenance processes are becoming more standardized.
Industrial IoT has made it possible to detect and investigate oil and gas leaks during transportation, using specialized drones and sensors. These drones are continuously sending and receiving data from remote sites and transferring it to their control centers. When equipped with thermal imaging systems, the same drones can be useful in detecting pipeline networks and anomalies within them – and early detection is the key to having secure oil and gas production systems. Production levels are easier to maintain as well, as secure communication pathways (through IIoT tech) are established among distributors, storage conditions, and possible public demands.
Farmers are now more aware of issues within the large-scale agriculture industry. Many farming facilities are part of a larger supply chain, so keeping on top of product and resource levels and provisioning is essential to ensure that the chain operates smoothly, and that resources are well managed. Along with internal information, the agriculture industry relies on the collection of data regarding weather conditions, soil or land information, greenhouse data, and other crop or livestock management details to be able to make clear and correct decisions.
Having data readily available to farms and livestock facilities saves time, cost, and labor which can be utilized in other aspects of an agriculture business.
Industrial IoT within agriculture can help with aspects of irrigation and fertilization, often automating these processes based on the crops’ needs. Real-time changes are quickly sent as updates to farmers and authorities in remote areas through industrial IoT applications and solutions – all powered by IoT SIM cards like the ones provided by Pod Group.
Animal tracking makes it easy for livestock owners to keep a close eye on the mobility and general health of their animals. Some livestock companies also manufacture and utilize microchips that continuously store and transmit data on the location and health data of their animals.