1. Introduction

Figure 1. Broad overview of IoT technology.

Figure 1. Broad overview of IoT technology.

Figure 2. Number of IoT Devices is Greater than Number of People.

Figure 2. Number of IoT Devices is Greater than Number of People.

2. Applications of IoT Devices

Figure 3. Number of IoT Devices Globally.

Figure 3. Number of IoT Devices Globally.

2.2. Healthcare Applications

The Internet of Medical Things (IoTM) is an emerging subfield that is changing the way healthcare is being delivered through the use of IoT technology (Joyia). The use of IoT technology in healthcare has come a long way and continues to be a promising area for growth. Essential innovations like the AliveCor heart monitor, which relies on IoT sensors, show how useful technology can be when applied to healthcare in efforts to save lives [33]. Advances in technology have always played a major role in healthcare and there are many different applications in which IoT devices are used in healthcare settings. One way that IoT devices are useful in healthcare is through the use of remote health monitoring in order to monitor patients at home rather than hospitals [34]. The information that is collected from IoT devices is helpful in the medical setting because it can be analyzed and used in ways such as early disease prediction [35]. IoT sensors even played a critical role during the COVID-19 pandemic in helping health workers better monitor critical parameters that could save lives if changes were detected right away [36]. By examining all of these different applications of IoT devices in the healthcare industry, researchers can find additional rooms to advance this field.

Figure 4. Connectivity of Different Medical IoT Devices.

Figure 4. Connectivity of Different Medical IoT Devices.

The use of sensors in healthcare is one way that IoT devices play a critical role in the delivery of healthcare services [37]. These sensors are basically acting as a bridge between the physical and information world by collecting a variety of types of data [5]. Sensors are crucial in helping healthcare professionals monitor different vitals that are important to measure in order to understand a person’s health situation and act accordingly. Medical sensors can be used in a variety of ways in order to measure crucial information. Medical sensors are connected to IoT and measure things such as temperature, respiration, heart rate, weight, skin conductance, galvanic response, blood flow/SpO2, glucose testing, muscle contraction, and motion analysis [38]. These sensors are connected to wireless sensor networks which relay useful information to different stakeholders involved in healthcare such as patients, medical staff, insurers, and more [39]. The use of medical sensors is vast and can be used in crucial medical equipment such as ECG monitors, glucose level sensing, and oxygen monitoring [40]. The goal of using any technology involved in healthcare is to promote better health outcomes and IoT devices play a critical role in promoting this. Recent advances in IoT-related technology will continue to play a deep role in creating stronger healthcare systems and the future of healthcare will become increasingly reliant on technology [41].

Medical sensors are important in collecting useful information about a patient’s health but this information is often very sensitive in nature and this makes privacy a major concern moving forward. Security has always played a vital role in IoT technology but it matters even more in a situation like healthcare where IoT devices will be collecting sensitive information about patients that is private in nature [42]. If a patient’s medical information were to get compromised, this could lead to consequences to those hospital organizations that did not employ the proper security measures to prevent it. The privacy and confidentiality of a patient’s medical information is a core concern when addressing the security vulnerabilities of healthcare IoT devices [43].

There are many issues that present a challenge to the successful use of IoT devices in healthcare and it is important to address these issues thoroughly when handling mission-critical operations like that of healthcare. Some important limitations that influence the use of IoT technology in medical devices include the need for high power consumption, availability of limited resources, and handling security issues from the large number of devices being used [44].

The use of IoT technology in healthcare is promising and exciting. There are many useful applications in which IoT devices can be used as sensors and this helps healthcare providers in a variety of ways. Moving forward, IoT technology will continue to expand and this will ultimately benefit healthcare organizations.

2.3. Agriculture Applications

As the population of the world grows at an exponential rate, the need for efficient food delivery systems is becoming a core issue that is a driver behind advancements in smart agriculture [45]. On top of the growing demand, things such as climate change and water scarcity have also played a role in increasing the demand for more efficient agriculture systems [46]. Much of the technology around IoT implementation aims to reduce resource wasting in agriculture [47]. The use of IoT technology in agricultural settings is critical in maintaining efficient operations and represents another common use-case of IoT technology. The demand for food supply chains that are of quality and quantity is important in feeding the world and having efficient systems built around these supply chains will benefit people all over the world [48]. The need for more efficient food-delivery systems is what helped promote IoT use in agriculture because stakeholders saw the benefits that technology could provide [49].

Figure 5. Different Types of Agriculture Applications for IoT.

Figure 5. Different Types of Agriculture Applications for IoT.

One way that IoT technology can be used in agriculture is automation. Automation involves having devices/objects respond automatically to different conditions without the need for human interaction. Wireless sensor networks are a key proponent in helping IoT devices achieve their automation goals [50]. This can be useful in massive operations like agriculture because of its sheer scale and need for efficient processes to maximize crop yields. For example, many sensors can be used in the soil of farmland in order to measure soil moisture content in order to build systems that make better use of water for irrigation purposes [51]. These IoT devices can be used to measure soil conditions such as water content and give an appropriate signal when it is low and turn on sprinkler systems automatically. Real-time monitoring and responses are very common and useful when understanding how IoT devices contribute to agriculture [52].

Data analytics is another area in which IoT has an important role in agriculture. Collecting and analyzing data is very useful because it can give important insights into how effective or ineffective an operation is. This data can be used to give stakeholders important insight that will ultimately impact their decision-making [53]. IoT devices collect massive amounts of data and this data is useful when analyzed over time to help aid in decisions about estimation and forecasting [54]. In particular, IoT devices can be used to gather massive amounts of information that will help those involved in agriculture maximize their yields. IoT devices contribute to the gathering of massive amounts of data that can be analyzed using machine learning methods that impact prediction, storage management, decision-making, farm management, and precision farming [45]. This data can become useful when trying to implement more sustainable farming methods through the use of data-driven decision-making [53].

Although there is a large demand for efficient agriculture, there are other factors in play that have affected the proliferation of IoT devices in this sector. One key component that affects how widespread IoT devices are in agricultural applications is how costly it is to implement them in farming operations around the world [55]. Massive farming operations would require a large number of wireless sensors to collect data about a farming operation and this can drastically increase the costs associated with implementing IoT in agriculture [56]. There are also many technical challenges that exist with implementing IoT technology in farms. Farms are often in large areas that are isolated and usually have poorer signals that impact their networking capabilities [57]. In addition to this, many farmers in rural parts of the world have limited knowledge of how to use IoT devices [58].

2.4. Smart-Home Applications

Smart home applications represent a promising use case in which people benefit from IoT technology and there are numerous advantages/disadvantages to consider. These smart home devices date back to the 1970s when the X10 protocol was first conceived and this technology allowed for smart home devices to communicate properly [59]. IoT devices in smart homes can be used in a variety of ways such as measuring home conditions, managing home appliances, and controlling home access [60]. Home automation remains a core feature around which IoT technology is applied to [61]. For example, there are numerous home appliances that can be turned on and equipped with IoT technology in order to become more efficient and convenient [62]. There are many benefits that extend beyond convenience. The use IoT sensors in smart homes can be used to assist the elderly in turning hard-to-reach devices on/off and even detect falls through the use of floor or camera sensors [63].

Figure 6. Smart Home Spending Statistics.

Figure 6. Smart Home Spending Statistics.

There are many techniques utilized in order to bring smart home technology to life. One important method relies on Radio Frequency Identification (RFID) systems being used in order to act as an enabler technology for IoT [64]. RFID is an important technology that helps in identifying objects, recording data, and even controlling individual targets through the use of radio waves [65]. RFID devices can be used in a variety of ways. For example, higher education institutions can utilize RFID technology in student identification cards [66]. RFID technology is also used to detect indoor roaming activity of the elderly and the data collected is used to give more insight into the health of elderly who live alone [67].

In an ideal future, IoT devices should be able to communicate with each other seamlessly [7]. There are many challenges that exist in the use of smart home IoT technology. Interoperability is one issue because the cost of using smart home technology is important to consider and integration of devices is one concern moving forward [69]. Different technologies utilized by IoT devices in order to create this connectivity include things such as WiFi, ZigBee, Z-Wave, Bluetooth LE, and Thread [68].

Security and privacy are also important to consider because smart grid technology can be a target for cyber attacks [69]. There are so many IoT objects that can be used in homes and this dynamic and heterogeneous nature of smart home environments presents a challenge when it comes to addressing authentication and privacy issues [19]. Cyber attackers could target items such as smart home routers, gateways, or any other IoT-enabled devices to access data [71]. Many strategies are currently being analyzed in order to address smart home security needs. Blockchain is becoming increasingly utilized because of its benefits of having a decentralized database based on cryptographic techniques [22]). Although blockchain approaches have benefited from decentralized security/privacy, there are drawbacks when it comes to the energy and computational overhead that makes it not ideal for IoT devices that are resource restrained [72].

2.6. Industry 4.0

The manufacturing sector is undergoing a revolutionary transformation with the advent of Industry 4.0, ushering in an era of intelligent and interconnected systems. A prominent trend in this domain is the rapid adoption of Industrial Internet of Things (IIoT) devices and sensors [90,91,92,93,94]. These embedded devices empower machines, equipment, and products to gather and transmit real-time data. The data generated by IIoT devices are invaluable for predictive maintenance, enabling manufacturers to proactively identify and address potential equipment failures, thereby reducing downtime and enhancing operational efficiency.

Another significant trend within Industry 4.0 is the heightened focus on cybersecurity. As factories and supply chains become increasingly interconnected and reliant on digital technologies, the need for robust cybersecurity measures has become paramount. Manufacturers are making substantial investments in advanced security solutions to safeguard sensitive industrial data from cyber threats, ensuring the integrity and availability of their systems. This includes implementing encryption techniques, authentication protocols, and intrusion detection systems to fortify critical information.

Artificial intelligence (AI) and machine learning (ML) are also playing a crucial role in driving Industry 4.0 forward. With the copious amounts of data generated by IIoT devices, AI and ML algorithms have the capacity to analyze and derive meaningful insights from vast datasets. Manufacturers are leveraging these technologies to optimize production processes, enhance quality control, and improve decision-making. By detecting patterns and anomalies in real-time data, AI-powered systems can optimize manufacturing operations, identify defects, and propose process improvements, ultimately resulting in increased productivity and reduced costs.

Furthermore, the adoption of cloud computing technologies has empowered manufacturers to securely store and access vast quantities of data in a flexible and scalable manner. Cloud-based platforms provide the agility required for data analysis, collaboration, and remote monitoring. Manufacturers can conveniently access real-time production information from anywhere, enabling remote troubleshooting, predictive maintenance, and streamlined supply chain management.

Collaborative robots, also known as cobots, represent another noteworthy trend in Industry 4.0. These robots work alongside human operators, assisting them in various tasks and augmenting productivity. Designed to be safe, adaptable, and easily programmable, cobots can adapt to changing production requirements. They are adept at handling repetitive and physically demanding tasks, freeing up human workers to concentrate on more intricate and creative aspects of the manufacturing process.

The integration of virtual reality (VR) and augmented reality (AR) technologies is also gaining momentum within Industry 4.0. These immersive technologies offer interactive and intuitive interfaces for training, simulation, and maintenance purposes. VR and AR enable workers to visualize and manipulate virtual representations of machinery, products, and processes, thereby enhancing training effectiveness and reducing errors.

Industry 4.0 is driving a transformative shift in the manufacturing landscape. The widespread adoption of IIoT devices, AI and ML algorithms, cloud computing, cybersecurity measures, cobots, and immersive technologies is reshaping traditional industrial processes into highly connected, intelligent, and efficient operations. Manufacturers who embrace these trends are poised to reap numerous benefits, including improved productivity, cost reductions, enhanced product quality, and increased agility in an intensely competitive global marketplace.

Figure 7. Industry 4.0.

Figure 7. Industry 4.0.

3. Challenges and Active Research Topics

3.1. Security of IoT Devices

The use of internet-of-things devices is becoming an increasingly larger part of the daily lives of people around the world; however, cyberattacks remain a large threat to the safe use of IoT [95]. Different examples of these devices are mobile phones, alarms, medical sensors, smartwatches, security systems, and more. The use of these devices continues to expand, and the need for strong security is vital to their success. Although these devices bring convenience, they come with many security issues and vulnerabilities. Since IoT devices often collect sensitive data, these data transmissions can be intercepted by third parties who intend to do harm or use this data for nefarious purposes. In one case, there were even attacks that could target IoT devices like the Mirai malware [96], which would hack/convert devices into its botnet and carry out DDoS attacks [97]. Malware like the Mirai and others take advantage of the vast amount of poorly protected IoT devices which commonly suffer from poor configurations and open design, and make them targets [98]. Detecting malware and IoT botnets remains an active research area, and many techniques are being applied. The use of a lightweight approach in the classification of IoT malware through the use of image recognition is just one example [99]. Other ways include the use of machine learning algorithms that use supervised, unsupervised, and reinforcement learning in order to handle tasks such as authentication, access control, and malware detection [100].

There is an enormous amount of data being transmitted on a daily basis which impacts critical operations across many applications. It could be possible for attackers to disrupt entire networks that rely on IoT technology, and the consequences would be devastating [101]. Hackers and criminals could seriously impact the expansion of IoT devices into the future, and it is crucial that security is thoroughly researched to mitigate these negative impacts.

Figure 8. DDoS attacks Worldwide.

Figure 8. DDoS attacks Worldwide.

4. Conclusions

Abbreviations

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