Fog computing: Shaping the Future of Smart Cities

Smart cities are developing rapidly along with technological innovation and the popularization of the Internet of Things, almost permeating every aspect of urban life. Ten years ago, there were only a few embedded sensors in cities, but now they are everywhere - from roads to thermostats and even trash bins. This ability to connect, communicate and remotely manage various devices has given rise to a new trend - fog computing in smart cities.

What is fog computing?

The term "Fog Computing" was first proposed by Cisco and refers to the extension of cloud computing to the network edge. Fog computing does not send all the collected data to the cloud. Instead, it means that the data will be processed locally on edge devices, and thus is sometimes also referred to as "edge computing". The urban technology system that utilizes this technology is called an edge computing smart city.

It is widely mistakenly believed that fog computing aims to replace cloud computing because the two concepts are complementary. Fog computing can be regarded as a type of hybrid cloud computing because they both provide storage, applications and data for end users. The key difference between the two lies in that the data of fog computing is processed and analyzed in fog nodes, such as distributed devices like industrial controllers, switches, routers and video surveillance cameras. These devices are structurally located between the cloud and the data source and can be said to be closer to the ground. This is the reason why the word "fog" is used in the name.

Fog computing: Shaping the Future of Smart Cities

According to Zion Market Research, the global fog computing market size is expected to reach 768 million US dollars by 2025. The latest data from Statista and other institutions show that the average cloud computing budget of various organizations this year is 42% higher than that in 2017. This trend reflects that the usage rate and significance of fog computing in smart cities will continue to grow globally and will thrive in numerous social sectors such as energy and utilities, healthcare, transportation, manufacturing, smart offices, and cities.

Fog computing reduces the burden on the network by improving its reliability and speed. For any smart city to maintain its leading position, it needs to deeply explore the next-generation Internet of Things, which means a comprehensive investment in fog computing is required. Fog computing not only helps manage data processing and brings many benefits to enterprise network security, but also brings significant economic benefits.

Delegating the decision-making power of these systems to the devices in the environment means that the cloud network does not need to manage a large amount of excessive data. On the one hand, this minimizes the cost of storing data to the greatest extent. On the other hand, it also ensures that only the most important information is processed, rather than a large amount of street lamp videos or railway station scan data.

The safety advantages brought by independent sensors should not be ignored either. When the work is accomplished by multiple different nodes in the system, the damage caused by network attacks or disruptions can be minimized. Given that 5G connections will still take longer to be realized, fog computing has become an exciting feature of today's smart cities.

Why has fog computing become so common in smart cities?

One of the greater challenges that smart cities continue to face is the vast amount of information generated, captured and analyzed every day. With the continuous increase in the number of Internet of Things (iot) automated devices, the amount of collected data has become difficult to manage and track, requiring powerful computing resources to process. Transmitting such a vast amount of data between the cloud and the data source is both time-consuming and expensive.

Fog computing can reduce the amount of data that needs to be sent to the cloud for processing, thereby improving efficiency. Smart cities can obtain the following benefits through fog computing:

Send the minimum amount of data to the cloud

The core goal of fog computing is to make big data smaller and easier to manage. According to IDC's prediction in 2019, by 2025, the amount of data captured by connected devices will exceed 79ZB. Fog computing can streamline such massive amounts of data by applying intelligent perception and filtering technologies, thereby transmitting only useful information based on the locally available knowledge of specific fog devices.

Low data latency

Fog nodes can process and load data without sending the data to a remote cloud server and returning the results. This significantly saves data transmission time and enables real-time response reception. Real-time data processing will become even more important for smart city systems, especially in situations where quick decisions or actions are needed: for instance, when emergency vehicles pass through the city, traffic lights can suddenly turn green to save lives.

Reduce bandwidth

Transmitting and processing data requires a large amount of bandwidth, and the bandwidth of cloud computing may be limited. However, for fog computing, this is not a problem because all the data is distributed among local devices rather than sent wirelessly. This can significantly reduce the consumption of network bandwidth.

Enhance data security

Data security is another key driving force for smart cities to shift resources to fog computing. It keeps more sensitive and confidential data away from vulnerable public networks, thereby preventing any cybercriminals from easily obtaining such data. Fog computing can detect malware and infected files at the device level in their early stages, even before they have a chance to infect the entire network.

What are some examples of edge computing in smart cities?

Smart cities are one of the best environments for the extensive implementation of fog computing, as tens of thousands or even millions of things in connected cities are generating heterogeneous data on various aspects such as road traffic, public safety implementation, waste management, and air quality.

Fog computing can quickly process and analyze all data, thereby operating these systems more effectively. The following are some examples of edge computing in smart cities:

Road traffic control

Smart cities utilize a wide variety of sensors to monitor and regulate road traffic. Sensors embedded in intelligent traffic signals can detect pedestrians, cyclists and passing drivers. Measure their speeds and the relative distance between them; Analyze all the collected traffic data; And according to real-time self-driving cars, they can also help drivers and pedestrians obtain assistance in emergency situations. The collected data can then be uploaded to the cloud for longer-term and more in-depth analysis.

The combination of fog computing and intelligent traffic lights has been proven to be highly effective in alleviating and reducing traffic congestion. For instance, a community in Bellevue, Washington State, has installed smart traffic lights that can respond to traffic conditions in real time: during peak traffic hours, the green lights will remain on for a longer time. Municipal officials estimate that this has led to a 36% reduction in travel time on the city's main roads and saved drivers between 9 million and 12 million US dollars annually.

SAN Leandro, California is another city that has launched an intelligent traffic signal project, which has achieved extensive integration of traffic signals with connected vehicles. This project was launched in 2017 and has significantly improved the timing of traffic lights.

Waste management

Garbage management is an extremely common challenge faced by cities because this process continuously consumes a great deal of time, money and resources. Garbage collectors usually clean the garbage bins on specific dates each month according to their schedules, but they do so without considering how much garbage is in the bins. Collecting garbage from almost empty trash bins is extremely inefficient because it leads to unnecessary fuel consumption and waste of manpower, while trash bins that are too full and left uncollected will dirty the streets. This makes waste management one of the most feasible use cases for the Internet of Things.

The application of intelligent sensors and fog computing will be able to monitor the city's garbage volume in real time and provide a more efficient garbage management method. The sensor installed on the trash can can identify when approaching the landfill volume and immediately alert the garbage collector when the landfill volume is reached. The landfill volume data can then be sent to the cloud for more in-depth analysis, thereby optimizing the routes and scheduling of garbage trucks.

Environmental control

Fog computing can monitor and analyze relevant environmental parameters and urban natural resources in real time. For example, the intelligent water management system can analyze water quality and detect any abnormal conditions, such as excessive nitrate or iron content. In addition, it can also detect water leakage and immediately notify the maintenance team that the leakage needs to be blocked or repaired.

The control and regulation of greenhouse gases is another application area where technology and fog computing are interconnected, aiming to improve environmental sustainability. Real-time collection and analysis of operational data enable the municipal government to understand the overall situation of greenhouse gas emissions, and thus take appropriate measures in a timely manner to reduce emissions. Based on these monitoring results, the government can remind citizens to reduce the use of heating or hot water at specific times to help reduce greenhouse gas emissions.

Monitoring system

Video surveillance systems equipped with intelligent sensors have made significant contributions to the security of urban streets. However, these systems constantly generate a large amount of information, which needs to be collected and analyzed in real time to ensure effective monitoring of public places. The traditional cloud model is difficult to meet these requirements because of the huge volume of data, severe latency problems, low network availability, and the need to continuously upload data to the cloud and return it, which is costly. Fog computing emerged as The Times required.

Fog computing enables the data collected by video surveillance cameras to be stored and processed in fog nodes close to edge computing smart cities. Its low latency feature can effectively monitor and detect any violent behavior in public places, such as busy airports or local shopping centers. Once an incident occurs, the security department will receive an alarm to take prompt action and even track down the fugitive criminals.

Fog Computing: The Future of Smart Cities?

Fog computing, with its ability to process various data quickly and safely, has great potential to become the next major trend in the development of smart cities. It helps collect data on a wide range of urban activities, from transportation to public utilities, ensuring everything operates efficiently and bringing sustainability to urban life. However, over-reliance on fog computing is not an ideal approach to handling these massive amounts of data. Therefore, cloud computing will still play a key role in the entire Internet of Things ecosystem.

Furthermore, fog computing does not imply the end of cloud-based standard Internet of Things networks. Centralized data is almost always more accessible, which in turn provides more ways for the private and public sectors to establish open data protocols. This can bring about more developed forms of innovation and digital creativity. Meanwhile, the data stored in the cloud also makes its uses more extensive.

Ultimately, fog computing is bound to play an important role in the next wave of smart city development. As this technology continues to move towards a system where computers can operate like humans, decisions made within devices will eventually become increasingly important for any smart city that attempts to stay ahead.