1. Tracking Valuable Equipment

Monitoring valuable equipment, such as firearms, radios, and body cameras [113], can help ensure that these items are always accounted for and not lost or stolen. The best way to track valuable equipment will depend on the specific needs of the organization. If accuracy is critical, then GPS tracking is the best option. If affordability is important, then RFID tracking or barcode scanning may be better options.

#### 2. Tracking Prisoners

Monitoring the location of prisoners who are on parole or probation can help ensure that they are complying with the terms of their release and not engaging in any criminal activity [114].

### 3. Tracking Stolen Vehicles

Monitoring the location of stolen vehicles can help law enforcement to quickly recover the stolen vehicle and apprehend the thief [115]. The best way to track a stolen vehicle will depend on the specific circumstances of the theft. If a vehicle has a built-in GPS tracker, it will be utilized to track the vehicle's location. If the vehicle does not have a built-in GPS tracker, a GPS tracker can be purchased and installed in the vehicle.

#### 4. Tracking Evidence

Asset tracking can be used to monitor the location of evidence in criminal investigations. This can help ensure that the evidence is properly secured and not tampered with [116]. Ultimately, asset tracking can help public safety officials to better monitor and manage their resources, leading to improved response times, reduced losses, and better outcomes for the communities they serve. Ultimately, public safety IoT applications can help reduce crime, improve emergency response times, and enhance public safety and security.

#### *2.5. Smart Water Management*

Nowadays, the demand for water continues rapidly as the population grows significantly. Since the last century, global water consumption is more than twice the rate of world population increase. The water usage is predicted to escalate 50% from 2007 to 2025 in the emerging countries and 18% in the developed countries [117]. By 2025, two-thirds of the world's population may face water shortages. A variety of enterprises depend on water for manufacturing and management. Absolutely, a large percentage of the wasted water due to the aging and leakage of the pipelines, for instance, according to the world bank, the annual global value of water produced and lost by utilities is close to \$14 billion [118]. To overcome this problem, smart cities must be capable of monitoring the water supply to ensure the delivery of adequate water supply to the residential and commercial buildings

(i.e., water saving systems). The smart cities are equipped-M2M sensors which could be used to remotely control and report any leakage in the pipelines. M2M sensors measure the flow of the water inside the pipes regularly, if an emergency triggered, the sensor transmits an alarming message to the M2M server to take the proper decision if the water leakage is beyond a normal range.

#### *2.6. Smart Health*

Deploying technology, data analytics, and other advanced techniques to improve healthcare outcomes and make healthcare delivery more efficient, effective, and accessible. Smart health applications include wearable devices, remote monitoring tools, telemedicine platforms, electronic health records (EHRs), and artificial intelligence (AI) algorithms. Remote Patient Monitoring, Telemedicine, Medication Management, Remote Surgery [119], and Asset Tracking [120]. The smart health care applications may be categorized into four major types:

#### 2.6.1. Tracking and Monitoring

Tracking is the function used to identify the moving patient (i.e., knowing the current position of the tracked person) [121]. For example, the tracking of the patients diagnosed with The Novel Corona Virus (COVID 19) pandemic and consequently those patients are subject to self-isolation [122]. For the government authorities to ensure that those patients are in self-isolating orders, they must be tracked using IoT sensors. In addition, to track the number of people interacting with the patient to contain the virus spreading. Regarding the monitoring, IoT smart health application allows the remote monitoring of the high-risk patients by attaching sensors [122]. These sensors send an alarm to the control center if the high-risk patient (who is vulnerable to fatal consequences due to critical conditions) has dangerous circumstances [123]. For example, if an elderly person falls or a diabetic person has hyperglycemia or hypoglycemia.

#### 2.6.2. Authentication and Identification

Authentication and identification in smart health are needed in multiple forms. Accurate patient identification is crucial and critical to avoid the assignment of wrong medication in terms of (dosage, time, frequency, route, and procedure). Authentication is an important security issue, especially with devices attached to the human body, for instance, the pacemaker, which is a small device placed underneath the skin in the chest to regulate the heartbeats [124]. If a hacker has the ability to intervene in the operation of the pacemaker by increasing or decreasing the heart rate, it will result in a life-threatening issue. In addition, the real-time medical data record, privacy, and maintenance must be authenticated to avoid the leakage of the patient data and to ensure the patient's privacy protection [125].

#### 2.6.3. Data Collection

Automatic data collection is required to reduce the processing and treatment time required to implement a medical treatment plan. If a medical device is attached to human body to measure the blood glucose for a diabetic patient, if the blood glucose in high, so sensor has to send the data automatically to the patient's physician (in the control center) to order the medication promptly. After that, physician sends the order back to the attached device to inject the enough insulin to consume the excessive glucose in the blood stream [126]. The previous situation is vital and represents instantaneous data collection and decision making. The energy consumption may be reported once at a time. The M2M applications may be delivered or reported in many ways:


#### *2.7. Smart Government*

Smart government utilizes technology and data to enhance the efficiency and effectiveness of government services, improve citizen engagement, and promote transparency and accountability. This approach involves the integration of various technologies, such as big data, artificial intelligence, the IoT, and blockchain, to create a more responsive and proactive government that delivers better outcomes for citizens. Smart government initiatives can encompass a range of areas, including public safety, transportation, healthcare, education, and environmental sustainability [78]. For instance, governments can use big data and AI to analyze crime patterns and predict criminal activity, improve traffic flow and reduce congestion through the use of smart transportation systems, or use IoT sensors to monitor air and water quality in real time. Smart government can also promote citizen engagement and participation through the use of digital platforms and tools that enable citizens to access government services and information, provide feedback, and participate in decision-making processes. This can lead to a more transparent and accountable government that is more responsive to the needs of its citizens. Overall, smart government initiatives have the potential to improve the efficiency and effectiveness of government services, enhance citizen engagement and participation, and promote transparency and accountability in government [127].

#### *2.8. Smart Building*

We are living in an environment surrounded by many electric and electronic appliances, for instance, television sets, microwaves, refrigerators, dishwashing machines, air conditioners, etc. To remotely control and monitor these devices, IoT sensors and actuators will be installed to efficiently utilize the energy consumed by these appliances. Heating and cooling might be adjusted using the IoT sensor depending on the current meteorological conditions to sustain the desired temperature [128]. The lighting may be adjusted based on the number of people occupying the room utilizing the motion sensor. The street lighting may be adjusted by utilizing the light sensors to save energy consumption. The motion outside the property will be detected using motion sensors which can be utilized to detect any burglary activity [128]. The electric appliances could be automatically switched off in case of inactivity mode (i.e., idle mode) to reduce energy consumption especially in the prime time. At the prime time, IoT sensors will contribute to the money saving due to the high price of the electricity during this time. On the other hand, the price at other times will be much cheaper than the price the prime time [129]. On the consumer side, the customers may sell the electricity during the rush hour and buy it or consume it during the non-rush hour time.2.9. Smart Manufacturing

Smart manufacturing is the integration of advanced technologies, such as the IoT, AI, machine learning, robotics, and big data, into industrial processes to optimize efficiency, productivity, and flexibility [130]. The main goal of smart industry is to create a fully connected and automated production system that is more efficient, flexible, and customizable than traditional manufacturing processes [131]. By using real-time data analytics and advanced automation technologies, smart industry enables businesses to optimize their operations, reduce costs, and enhance product quality [132].

#### 2.8.1. Predictive Maintenance

Predictive maintenance (PdM) is a maintenance strategy that uses data analysis to predict when equipment is likely to fail. This allows maintenance to be scheduled proactively before a failure occurs. PdM can be a valuable tool for smart manufacturing, as it can help to improve uptime, reduce costs, and increase reliability. Employing sensors and AI are used to predict when equipment will fail and contribute to preventing costly downtime [133].

#### 2.8.2. Digital Twins

Creating virtual models of physical assets helps optimize performance and reduce maintenance costs [134]. Overall, smart industry represents a major shift in the way businesses approach industrial production and has the potential to transform entire industries.

#### 2.8.3. Industrial Internet of Things (IIoT)

Connecting machines, sensors, and devices throughout the manufacturing process to collect and share data in real time enables better monitoring, predictive maintenance, and process optimization [135].

#### 2.8.4. Big Data Analytics

Big data analytics is a powerful tool that can be used to improve a variety of processes in smart manufacturing. It is still important to have a good understanding of the manufacturing process and to use big data analytics in conjunction with other tools and techniques. Utilizing large volumes of data collected from various manufacturing processes helps gain insights, identify patterns, and make data-driven decisions [136].

#### *2.9. Unmanned Aerial Vehicle (UAV)*

UAV is a type of aircraft that is operated remotely without a human pilot on board. UAVs can be either controlled by a human operator on the ground or can be programmed to operate autonomously. They are commonly used for military, commercial, scientific, and recreational purposes and have become increasingly popular in recent years due to advances in technology and lower costs. UAVs equipped with IoT sensors can collect and transmit data in real time, enabling a variety of use cases across multiple industries [137].

#### 2.9.1. Agriculture

UAVs equipped with sensors can be used to monitor crop health, collect data on soil moisture and nutrient levels, and identify areas in need of irrigation or fertilizer [138]. This can help farmers optimize their crop harvest, reduce costs, and minimize environmental impact. Eventually, UAVs can provide farmers with valuable data that can help them make more informed decisions about crop management, leading to higher yields, and increased sustainability. UAVs have a wide range of agricultural services including:

#### 1. Crop Monitoring:

UAVs can be used to monitor crops for pests, diseases, and nutrient deficiencies. They can capture high-resolution images of the crops, which can be used to detect early signs of stress and other diseases based on AI algorithms [138]. In addition, these images may be utilized to identify the ideal time to harvest different crops.

#### 2. Precision Agriculture:

UAVs equipped with specialized sensors can provide farmers with data on soil moisture, temperature, and other environmental factors. This data can be used to make more informed decisions about crop management, including planting and irrigation [139].

3. Crop Spraying:

UAVs can be used to spray crops with pesticides or fertilizers, which can reduce the need for manual spraying and minimize the risk of exposure to harmful chemicals [140]. Eventually, UAV-based crop spraying offers a number of potential benefits [141]. However, there are also some challenges that need to be addressed before they can become widely adopted [142].

#### 4. Mapping:

UAVs can be used to create high-resolution maps of farms, including the layout of fields and buildings. This data can be used to plan future planting and construction projects [143]. They offer a number of advantages over traditional methods, such as ground-based surveying, and include accuracy, efficiency, and safety.
