All other technologies are part of smart city operation, although in different forms. However, compared with the Internet of things, it has little connection with the concept of smart city. That's because smart cities and related smart engineering governance rely on the collection, analysis and processing of a large number of small real-time data, which can only be realized with the help of IOT sensors.

IOT sensors and cameras can continuously collect detailed information in real time in various forms. Different types of IOT sensors can be used to collect data in real time, such as people flow in railway stations, traffic conditions on roads, pollution level in water sources, energy consumption in residential areas, etc. By using these data, government agencies can make rapid decisions related to the allocation of different resources and assets.

For example, according to the passenger flow and ticket information of the railway station, the transportation organization can rearrange the train route to meet the changing needs. Similarly, the health, safety and environment agency can monitor the pollution level of water bodies and notify the responsible personnel to take remedial measures. In some cases, IOT actuators can automatically initiate response measures in an emergency, such as stopping the supply of contaminated water to domestic households.

Therefore, Internet of things networks and sensors will essentially constitute the neural system of smart city, transfer key information to the control entity, and relay the response command to the appropriate endpoint.

2. Big data analysis
The application of smart engineering city in all aspects will be mainly data-driven. All decisions, from long-term strategic decisions such as public policy to short-term decisions such as assessing the welfare value of each citizen, will be made through the analysis of relevant data.

With the help of IOT sensors and other advanced data collection methods, with the increase of the amount, speed and types of data generated, the demand for high-capacity analysis tools will be greater than ever before. Big data analysis tools have been widely used by the government, from predicting the possibility of crime in specific urban areas to preventing crimes such as child trafficking and child abuse. As the Internet of things can collect data from a large number of new resources, big data analysis will be used in all key areas, including education, health care and transportation.

In fact, big data analysis has become an integral part of the Internet of things, and may be included in the Internet of things in the future. Big data enables the government to understand the data it has by discovering patterns that reflect urban trends.

For example, big data analysis can help the education sector find trends such as low enrolment, so as to prevent such results. Big data can also be used to find the cause of such problems and plan remedial measures. Therefore, big data will become the key decision support of smart city government.

3. Artificial intelligence
Artificial intelligence will be based on the Internet of things and big data functions. Artificial intelligence can support big data and Internet of things plans of smart cities through automated intelligent decision-making.

In fact, the ability of the Internet of things to initiate responsive action will be largely driven by some or other forms of artificial intelligence. In smart cities, the most obvious application field of artificial intelligence is to automate the execution of a large number of data intensive tasks, such as providing basic citizen services in the form of chat robots. For example, AI based chat robots can be used to process simple requests, such as:

(1) . provide new water, electricity and gas connections
(2) . change property ownership details
(3) . and changing addresses and other registration details on government records

However, the real value of artificial intelligence can deal with the problems faced in the operation of smart cities by using advanced AI applications such as deep learning and computer vision. For example, traffic managers can use computer vision to analyze traffic pictures to identify drivers' illegal parking. Computer vision can also be used to find and report vehicles related to criminal acts to help law enforcement agencies track criminals.

Deep reinforcement learning can also be used to automatically optimize resources according to emerging needs in smart cities. With the help of reinforcement learning, the government can improve its operational efficiency, because these AI systems can become better by experience.

4、 5g
Smart engineering city is built on the real-time communication and information sharing capabilities of different departments to ensure complete synchronization in operation. By achieving this synchronization, governments can ensure that their citizens have timely access to key services, such as health care, emergency response and transportation. Thus, it can not only ensure the convenience of citizens' urban life, but also improve their safety and overall well-being.

For example, in the event of an emergency such as an explosion or fire, real-time communication between fire departments, urban ambulance services and traffic control departments can ensure perfect real-time coordination among these entities, so as to minimize casualties.

In order to achieve this seamless communication between different government entities, it is very important to have a communication network that can handle a large number of communications with low delay and high reliability. Although a large amount of data is shared in real time, by using 5g communication technology, the government can ensure that all government agencies can work together seamlessly.

5. Augmented reality
Providing timely services to citizens means ensuring that government personnel are provided with the information they need to carry out their tasks effectively. For example, doctors in government health centres must be provided with information about the patients treated. Alternatively, the track layout should be updated for the workers responsible for repairing the damaged railway line and the location of the damaged parts should be accurately determined.

By using AR headgear, such information can be forwarded to workers immediately and in real time when they need it. This can minimize the effort and time required by workers to find the necessary information. So that they can take immediate action. Traffic managers can also use AR to obtain real-time information about illegal parking and stolen vehicles through smart glasses or smart phone applications, so as to provide the efficiency of urban traffic operation and management.