IoT is the current mainstream trend in technology. In this way, we will discuss the industrial changes and market opportunities of the digital revolution, and will further analyze the technology and application fields of IoT.
From M2M to IoT Technology:
Machine-to-Machine (M2M) is a mode or system in which machines and devices communicate directly through the network to complete tasks by themselves without human intervention. The technology of M2M has been developed for a long time and can be traced back to the early 20th century. However, the GSM (Global System for Mobile Communications) launched in the 1990s brought M2M communication into a new stage of development.
M2M can be used to capture and transmit data according to specific applications through multiple wireless technologies (LTE, WiFi, BLE, ZigBee, RFID). Often more than one wireless technology is used in each application or solution, and different wireless technologies are used for data capture and data transfer (for example, ZigBee and LTE, RFID, and WiFi). Through these tools, you can connect mobile or stationary objects, such as trains, household appliances, medical equipment, monitors, etc., and complete related tasks. Includes sensing or data capture, wireless data transport, and information management system.
IoT can be imagined as an advanced version of M2M. Internet of Things (IoT) is a network type that enables objects to communicate and perceive each other with the surrounding environment through embedded technology. But basically, it still stays in the connection, communication, and data interaction between electronic devices. Subsequently, the definition of IoT began to focus on the use between humans and electronic products. Therefore, in addition to the sensors of electronic products, the data collection and usage patterns of human use of electronic products are also included in the definition of IoT. In addition to being connected to the product, it can track various usage data of the user, such as the user's biomarker.
The real value of IoT lies in its ability to leverage entirely new data sources and data types to enable entirely new business models, industry insights, and lifestyles. Overall, IoT is a general term that includes a variety of industries and technologies, each of which is very important and has its domain that needs to be studied. For example, IoT includes CIoT (Consumer IoT) and IIoT (Industrial IoT). The main difference between CIoT and IIoT lies in the types of devices and APPs, the technologies that drive these devices, and the goals to be achieved.
Consumer IoT (CIoT):
CIoT is consumer-related APPs, Use Cases, and devices. CIoT has a wide range of applications, from personal fitness equipment to smart home automation, and its functions and applications are also very diverse.
Industrial IoT (IIoT):
IIoT refers to the use of IoT in industrial applications. Overall, IIoT focuses on the integration of M2M communication, big data, and machine learning (ML), to improve the efficiency and reliability of factory operations. The scope of IIoT covers overall industrial applications, including production processes, software, and hardware collaboration, medical equipment, and robotics.
Over time, IoE (Internet of Everything) technology has been proposed, which means that in addition to analyzing the data exchanged in electronic devices or devices with sensors, it can also integrate data when humans use these devices, and make value judgments and feedback information. In addition to IoE, IoB (Internet of Behavior) technology has also developed. IoB collects and provides important information about customer behavior, interests, and preferences, attempts to understand customers through this data, and uses this information to modify, develop, and promote products or services. After the data is collected, it is fed back to other devices through analysis.
Nowadays, there are all kinds of data devices around us, collecting digital dust at any time, and this digital dust can study the relative relationship between each behavior and behavior. IoT technology is used to collect data and analyze feedback information.
Industry 4.0: IT, OT, IIoT
The global manufacturing industry is moving towards intelligence. Industry 4.0 is based on IIoT and CPS (Cyber-Physical Systems), and the goal is to make the processes in the manufacturing supply chain intelligent. CPS refers to the combination of digital and physical. From the point of view of the mechanism, it is to input the mechanism of the physical world into a virtual world (computer) for simulation and modify it in the computer until it succeeds. Real production in the physical world.
The manufacturing industry expects to integrate IT (Information Technology) and OT (Operation Technology) through the implementation of IIoT to integrate the operating system of the manufacturing site and the information system of the enterprise. OT is the earliest system, and its responsibility is to establish and maintain control processes such as manufacturing plant or production environment site and execute them accurately in an isolated and independent network. Later IT technology is mainly responsible for data generation, file storage, transmission, file capture, and protection. With the development of digitalization in the manufacturing industry in recent years, these operating systems that used to be independent of each other are gradually being integrated. For example, automatic monitoring of transformers, smart meters, physical operation information of machines, etc. through IIoT, the network, and digital communication are integrated into OT middle.
The integration of IT and OT, with IIoT and CPS, the whole process is a slow process. In addition to the technical level, the more important factors involved are the cultural integration of the two departments, which involves the originally unrelated departments. collaboration, the convergence of IT and OT is progressing extremely slowly. The issue of the attribution of its responsibility has become the biggest obstacle to its integration.
The Technical Scope and Application Field of IoT:
According to statistics, the market value related to IoT will grow from $35.7 billion in 2019 to $83 billion in 2026, with North America accounting for the largest market. The size and growth rate of the market value mean that there will be many booming business opportunities for IoT in the future.
The growth rate of IoT in various industries, the industry with the highest estimated output value in 2025 is the security/fire alarm field, which is about $175 billion, and the fields with an estimated output value of more than $50 billion in 2025 include vehicle head union, personal portable electronics, payment processing. The highest growth rate is about 60% for retail delivery robots and nearly 40% for autonomous road vehicles and agriculture.
Even with the impact of Covid-19 in 2020, the output value is still $724 billion, with sensor/module being the largest at 28.6%, followed by ongoing service at 21.3%. The annual growth rate in 2020 is as high as 8.2%. By 2030, the IoT output value is expected to reach $1.5 Trillion, of which Consumer IoT will reach $650 billion.
In 2030, the advantages of IoT have shifted from the largest hardware industry to the service industry, accounting for 34% of the hardware and 66% of the service respectively. At this time, the IoT service industry has accumulated data from the past few years, and in the next few years in 2018, continued to collect and optimize the data model and began to turn to the business model of selling data and services to further assist the digital upgrade of various industries. While the smart city will have a production value of $135 billion in 2021, small retail will have a production value of $43 billion in 2024.
Factors Driving IoT Development:
- Sensors: The cost of Sensors, as the technology matures, continues to decline, enabling manufacturers to deploy sensors at lower prices.
- Computing Power: Computing Power keeps improving.
- On-Demand Cloud Computing: The improvement of On-Demand Cloud Computing, including Amazon Web Services (hereinafter referred to as AWS), Microsoft Azure, Google Cloud Platform, and Alibaba Cloud, has continuously increased the volume and output value of its services.
- Connectivity cost: The sharp drop in Connectivity cost enables more and more information to be easily and cheaply connected to the Internet.
- Digital Business Model: The birth of the Digital Business Model, which is based on the use of digital technology to create value for customers, and allows customers to pay for purchases at a lower threshold. For example, Equipment as a Service (EaaS) is a business model in which equipment is leased to end-users for a period, which is different from the traditional one-time selling equipment business model. For example, the customer no longer buys the engine but rents the engine, and the manufacturer is equipped with enough sensors on the engine. In the future, the data monitoring, maintenance, and repair of the engine will be the responsibility of the manufacturer. There will be many IoT manufacturers transitioning to EaaS.
- Customers can reduce installation costs.
- In the process of transitioning from the original business model to Subscription, it has more mature financing tools.
- New competition from third-party service providers.
- Evolving Partnership: In the IoT industry, evolving partnerships must have a global market vision at the beginning of the business.
- Advancements in Connectivity Technologies: Advancements in connectivity technologies enable IoT to be connected in a more suitable way, such as the development of LPWA, 5G, etc.
- Flagship Government Program: Flagship government program promotes smart digital transformation, such as a smart city, the government injects a lot of resources and develops various uses.
The Benefits of Importing IoT and User Experience Feedback:
The proportion of IoT introduced in various industries has increased year by year. Many IoT has been introduced in the retail industry, transportation industry, government, and health care. Among them, 64% of the retail industry uses IoT to optimize supply chain optimization, and 56% of them use IoT to optimize supply chain optimization. The transportation industry uses IoT for fleet management, 58% of government departments use IoT to solve public safety issues, and 66% of health care industries use IoT to track patients, staff, and inventory.
In addition to the above, manufacturing is the industry that is most actively introducing IoT. The top five applications of IoT in manufacturing include industrial automation, quality and compliance, production planning and scheduling, supply chain and logistics, and plant safety and security. The manufacturing industry is actively introducing IoT, expecting to improve the efficiency of factory operation.
The benefits of introducing IoT include increased efficiency, increased yield, and improved quality.
The Technology Combination of IoT and AI:
IoT is combined with AI from the initial sensor collection to the analysis results. When an environment is equipped with multiple sensors, which can sense temperature, pressure, human behavior, air quality, etc., and put the sensed results into the AI system, the AI system will perform Data Gathering and analyze the results through big data. Use algorithms to build modeling, and finally decide. At this point, the work processing of the AI system has come to an end, and then the best decision is informed to the sensor and the environmental system, and the environmental system takes the action.
In AI/IoT, there is a key technology that can make AI analysis and IoT more closely connected, and give real-time feedback (take an action) to the currently perceived data. This key technology is called Streaming, also known as Real-Time Reaction.
What is an IoT Solution Architecture?
- Hardware: Contains sensors, gateways, etc.
- Connectivity: It includes wireless network, wired network, short-distance network, long-distance network, etc.
- Software: It contains IoT Platforms and Different Layers.
- Security: It integrates the security guarantees mentioned above.
Overall, the IoT platform needs to transmit data to the AI platform. The AI platform processes the data through machine learning (ML) and then feeds decision-making information back to the IoT platform.
Importance and needs of IoT Security:
IoT is perfect both in terms of function and application, but why is there no way to import it 100%? The main factor is IoT security.
If there is no IoT Security, it will affect the development of the industry and the technical protection of enterprises, information privacy, and other issues. At present, about 98% of IoT message transmission channels are not encrypted, 57% of IoT devices are poorly protected against attacks, and 83% of medical imaging devices run in an environment that does not support operating systems, resulting in numerous loopholes. That is why many hospital systems are hacked, the main reason is that the system is too fragile. The cost of leaking sensitive data is very high, especially in the field of healthcare, which means the importance of IoT security, and it also means that IoT security must be solved first to improve the effectiveness of IoT introduction.
4 Layers of IoT Security:
The Development Trend of IoT Security:
- Layer 1 - Hardware Layer:
When it comes to IoT, the first thing to discuss is the hardware with sensors. Therefore, physical security is the primary way to develop IoT. At the hardware level, the most important thing to pay attention to is the device identification of IoT devices, which is to create unique ID cards for these devices. From manufacturing, and distribution to patient use, its source and identity can be known. The purpose of this move is to improve patient safety and realize monitoring of medical equipment after-sales.
- Layer 2 - Secure Communications:
This layer includes Firewall, Intrusion Detection (IDS), Intrusion Prevention (IPS), and End-to-End Encryption. To set up a Firewall is to set up a gateway that can be monitored and managed between the intranet of the IoT and the Internet, to control the entry and exit of all network packets, and to allow or prohibit specific data access behaviors on the network. Its main job is to check all passing IP packets and control the transmission of network information packets by IP address, port, and packet transmission direction.
The main function of the intrusion detection (IDS) system is to monitor and detect network packets and monitor the network and system operating conditions according to the preset Security Policy. Various attack attempts, attack behaviors, or attack results. The intrusion prevention (IPS) system turns passive into active. When abnormal packets or behaviors are found on the network, the system not only sends an alert to the network administrator but also immediately takes necessary measures, such as blocking the source IP. End-to-end encryption, as a secure communication method, prevents third parties from accessing data when one end device transmits data to another end device. This is a communication system in which data can only be read by both terminals, to prevent eavesdroppers. Due to many IoT devices and frequent communication with other IoT devices, the importance of end-to-end encryption is important on IoT devices.
- Layer 3 - Secure Cloud:
Cloud security refers to a broad set of policies, technologies, and controls used to protect data, applications, and cloud computing infrastructure. When data or information is sent to the cloud, it is difficult to protect it, especially now it is more difficult to use multi-cloud. A hybrid cloud is to use multiple providers (AWS, Azure, Google Cloud) at the same time. Data hosting, storage, and implementation of the application stack.
- Layer 4 - Secure Lifetime Management:
In IoT, it is not only hardware, communication security, and cloud security that deserve attention. The overall life cycle security management is very important. In short, when is the patch, upgrade, update, how to update, upgrade, and how to maintain, these issues cover the security management of the entire life cycle of IoT devices from manufacturing to sellers until the devices are safely retired. From the perspective of security, security management is crucial.
- Old IoT devices are targeted by hackers: Because older devices are not continuously updated and not protected, they are prime targets for hackers.
- Open Source has its benefits, but the downside is that it is easy to be targeted for malicious attacks, and the report recommends against using newer open-source platforms unless they have proven themselves to be safe from breaches.
- The software development team must take security considerations into account at the beginning of the design, and cannot do it after the fact.
- Beware of API Vulnerabilities: Because the API provides a simple access system, it is easy for hackers to attack the API. Developers need ways to better secure API authentication and develop authorization processes. Simply put, an API is a combination of different things, and every street corner is a big hole for hackers to take advantage of.
- Tools for application security must be more responsive while being able to scale to cloud environments and provide an operational means to remediate vulnerabilities quickly. Cloud security itself has huge loopholes, and how to avoid them is a big issue.
The Future Trend of IoT and the Challenges Encountered by IoT Startups:
- IoT Security: As the most vulnerable IoT device and network, IoT security is the biggest pain point.
- Manufacturing: More and more manufacturers are investing in IoT manufacturing.
- Big Data Analytics and ML: The collection of data and the application of AI algorithms are often used in conjunction with IoT.
- Healthcare: There are many IoT applications in the field of healthcare, but in the future, there will be more digital health devices that will capture human biomarkers in a more comfortable and non-sensing way.
- Workforce Management: Workforce management is the process of maximizing an organization's performance levels and capabilities. In the future, this process will be optimized through IoT to enable all activities required to maintain a productive workforce such as field service management, human resource management, performance, and training management, data collection, recruitment, budgeting, forecasting, planning, and analysis, etc., are monitored and optimized in real-time through data analysis and AI.
- Smart City: In a smart city, problems such as traffic congestion and disaster notification can be optimized through IoT.
- Cloud: IoT is connected to both data and computing. Cloud is an inevitable trend, so major giants regard cloud as the key.
- Customer Service: The future business model will be based on services, one of which is Equipment as a Service, and must be equipped with IoT devices to collect usage data, monitor, and maintain. It can be foreseen that once the IoT is connected to the Internet, future customer maintenance will be IoT and software automatic.
- Developers to come up with IoT milestones: For IoT developers, where each step of IoT can be done developers have a bottom line, but the infinite applications of IoT and innovation of business models, such as cooperation between vertical fields, etc., all need to be taken into consideration.
- Powering Smart Stores: Smart stores, or unmanned stores, used to think that unmanned stores would be tied to the blockchain, using small chips and mobile phones to achieve automatic checkout.