The Future of Smart City Technology: Artificial Intelligence, Big Data, and Cloud

2024-03-05

More than half of the world's population is attracted by the attractiveness of cities - the growth of prosperity, employment, opportunities, education, and entertainment is irresistible. Urban planners and entrepreneurs drive this development by providing necessary services and businesses to citizens, thereby driving rapid expansion of urban areas.

In turn, this has led to demands such as sustainable development goals, intelligent density, and intelligent technology to adapt to the constantly changing needs of citizens. However, the outbreak of the COVID-19 pandemic crisis has exposed the quality of urban governance, the degree of inequality and the ability of cities to adapt to emergencies overnight.

The Covid-19 crisis exposed the historic isolated development model of many urban sectors, where various sectors such as public safety, e-government, communication, transportation, electricity and water, municipal services, environment, and logistics lack sufficient collaboration and adaptability to protect their residents. Therefore, it is necessary to digitize urban services, in which information and situational awareness can be obtained in almost real-time from all necessary data sources to make informed decisions.

Nowadays, the digital transformation of smart cities will follow the concept of "equipment pipeline cloud application". Equipment collection data; Pipelines transmit data through transportation infrastructure to the cloud, where it is stored, classified, and correlated, and can be used for processing for visualization to make informed decisions. Thisa simplified model, but it can be applied to any vertical industry in smart cities, and the key is a cloud based collaborative digital platform that can adaptively process and make decisions based on classification, accessing all data in the "data lake".

One of the cities where Huawei adopts these principles to develop smart city solutions is Yanbu, Saudi Arabia. A multi-stage approach was adopted, starting from the equipment connecting various subsystems of infrastructure, including traffic, monitoring, intelligent lighting, help points, parking, and environmental monitoring. The further stage focuses on digital platforms to provide effective municipal collaborative management, high-quality public services, and promote sustainable economic development. The Yanbu Smart City project won the prestigious "Data and Technology Award" at the 2017 Smart City Expo held in Barcelona.

Why Cloud is the Core of Successful Smart Cities

Each department in the city has many existing systems to meet their respective services and can be migrated to the cloud in stages. The first stage will be upgrading infrastructure to achieve device connectivity and information exchange between government entities. The second phase will create a shared digital platform in the form of a hybrid cloud that meets both private and public needs. There are many benefits to a cloud environment, including information sharing, resource sharing, load balancing, higher availability, cloud computing, single monitoring and maintenance operations, elastic scalability, and reduced total operating costs.

In addition, one of the powerful features is the ability to improve the quality and efficiency of paperless services by introducing process automation, especially automated services enhanced by artificial intelligence (AI). By adding AI to the "Device Pipeline Cloud Application" model at each level, we can achieve intelligent interaction, intelligent redundancy, and self-healing connections of devices, feed data to intelligent cloud centers for data processing, and contribute to the development of new smart cities.

One service provided by Huawei on Huawei Cloud Services (HCS) is to train the requirements of online clouds and then infer adaptive algorithms based on edge based neural computing technology to adapt artificial intelligence functions to specific customer needs. We call it Enterprise Intelligence (EI). There are dozens of pre trained human like API algorithms that can be combined to create and train customer specific intelligent routines required for smart cities and any vertical industry.

Some of these APIs include image recognition, optical character recognition, natural language processing, speech to text (and vice versa), image search, and video content viewing, among others. Once the data provided by the customer is trained, these algorithms will be applied on-site at the required level of intelligent twin smart cities.

An example of how to effectively utilize smart twin smart cities is intelligent transportation management. By using various sensors to collect sufficient data from all major traffic arteries in a city, intelligent digital twin models of traffic flow can be created in almost real-time, and then managed to optimize efficiency. This has been successfully implemented in the big city of Shenzhen, China, reducing average congestion time by 12% during peak hours and increasing average vehicle speed by 6%. In addition, by creating a green channel, the time for emergency services to reach events has been reduced by 40%.

Other usage methods include using robots for automatic visual garbage classification, using drones equipped with cameras for visual inspection of power lines, autonomous robots patrolling cities for public safety inspections, and collecting municipal visual inspection data. The purpose of all EI implementations is to improve the productivity, efficiency, quality, and safety of services, and should always include a process of ethical checks for deviations, responsibilities, and inequalities.

Rich data

The key to the transformation of smart cities is to utilize a large amount of available data to assist AI assisted digital platforms in making informed decisions. By successfully utilizing this data, cities can provide situational awareness, productivity for automation and optimization of repetitive processes, enable prediction and prediction models, and simulate intelligent digital twin environments for better management. The user interface that visualizes all of this information is the Intelligent Operations Center (IOC) application, which uses 3D geographic information systems and augmented reality to provide an interactive dashboard for all activity and statistical information.

In addition to applying the simplified principles of Device Pipe Cloud Application mentioned earlier, the key technologies for future smart cities are simple: artificial intelligence, big data, and cloud (ABC), combined with 5G as the transmission medium. These together provide the future demand for digital transformation. This makes smart cities an ideal testing platform for innovation based on digital cloud platforms, which are agile and adaptable to volatility, uncertainty, complexity, and ambiguity - the so-called VUCA principles may become new guidelines. Priorities include adhering to sustainable development principles, prioritizing circular economy, adapting to climate change, and equity principles.

Now, many of us have created new remote work or learning routines through countless conference calls, and we may start to see environments moving from cities to more rural areas. Although it is impossible to predict what the new normal will be, it is likely to be reverse urbanization. The question is not whether cities will continue to prosper and develop, but whether we will have the imagination and vision to digitize cities and bring about the safer, more sustainable, intelligent, adaptable, and resilient lifestyles we have always needed.

What does deep learning mean for autonomous vehicle?