How Are Smart Cities Made ‘Smart’: Top 6 Enabling Technologies | Hacker Noon

Smart cities are developed with the help of various information and computational technologies, particularly wireless sensor networks, the Internet of Things(IoT), and cloud computing. Smart cities comprise an enormous amount of sensors that are continuously generating data. The top 6 enabling technologies include big data analytics, IoT, blockchain, smart dust, cloud computing, and smartphones.

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Smart cities are developed with the help of various information and computational technologies, particularly wireless sensor networks, the Internet of Things (IoT), and cloud computing. 

Urbanization is expected to rise by almost 70% in 2050Frost & Sullivan‘s research estimates a market potential of $1.5 trillion globally for several sectors of the smart city.

Victoria Fernandez-Anez formally defines smart cities in her work as:

“A Smart City is a system that enhances human and social capital wisely using and interacting with natural and economic resources via technology-based solutions and innovation to address public issues and efficiently achieve sustainable development and a high quality of life based on a multi-stakeholder, municipally based partnership.”

The Architecture of Smart Cities

The vision of a smart city encompasses every aspect – be it health, governance, finance, environment, and education. The technologies utilized are the Internet of things (IoT), smart-phone, Radio Frequency Identification System (RFID), smart cards, semantic web, cloud computing, collective intelligence, smart apps, and Artificial Intelligence (AI).

The smart city’s architecture is a layered infrastructure consisting of the sensing layer, the communication layer, and the application layer.

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In the above figure, the bottom layer is the sensing layer that provides the data to the next layers for normalization and further processing. The communication layer provides the information flow between the sensing layer and the application layer.

Jin et al. have explained data flow in four main steps:

  1. Data collection
  2. Data processing
  3. Data management
  4. Data interpretation

The real-time sensing of the data needs to be implemented in multiple sensing paradigms. This, too, has a connotation with network traffic, data storage, and resource utilization. After data collection, it needs processing and management. The last step in the data flow is at the application layer that is data interpretation. 

Enabling Technologies

Several technologies work in collaboration to run the smart cities. These enabling technologies are listed below:

1. IoT (Internet of Things)

Internet of things is a communication paradigm where wireless sensors are deployed in the field to sense and acquire important data and forward it via the Internet to data processors for advanced analysis. IoT is a potential enabling technology for smart cities as it seamlessly connects hybrid devices like resource-constrained sensors (RFID Tags), smart devices, gateway devices, and electronic devices (cameras, microwaves, refrigerators) to data processing sources through heterogeneous communication protocols. 

2. Big data analytics

Volume, variety, and velocity – In a smart city, there are an enormous amount of sensors that continuously generate data. To convert this data into a serviceable artifact, data management techniques must be employed. There are four phases of data management: data sensing and gathering, data fusion, processing, and aggregation, data exploitation, and service delivery. 

Along with big data, open data is another data analysis technique that is useful in smart cities applications. Open data means that data is freely available to people, organizations, and companies to reuse and develop value-added applications.

3. Smartphones

Smartphones are an essential component of smart cities infrastructure. Our smartphones contain a lot of tiny sensors which continuously generate raw data and provide context-aware information to the users. Smartphones are enabled with technologies like 5g/4G/Long-Term Evolution (LTE) networks which allow connectivity everywhere and at very high speeds and are used as relay devices.  

4. Smart Dust

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Image Source: Austin Ban (Unsplash)

Smart dust is a name given to tiny computational objects consisting of Microelectromechanical Systems (MEMS). These objects are capable of detecting and sensing even slight variations in the environment like physical vibrations or chemical changes.

These objects can be installed in the environment in a non-intrusive way, such that they do not interfere with the regular activities of the environment in which they are deployed. Smart dust can be used to perform applications like habitat monitoring, indoor and outdoor environmental monitoring, security and tracking of people and objects, traffic monitoring and management, human health and well-being monitoring, etc.

5. Blockchain for Smart cities 

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Image Source: Stanislaw Zarychta (Unsplash)

Urban culture involves a lot of data and information exchange between stakeholders. Blockchain enables network participants to exchange data with a high degree of reliability and transparency without the need for a centralized administrator. Economic applications of smart cities such as smart contracts can get the most out of blockchain. 

6. Cloud Computing

Sensors embedded in smart cities applications generate an enormous amount of raw data in real-time that needs to be processed in an efficient way to produce informed decisions. In this regard, cloud storage services offer huge storage and faster computational capabilities. Smart cities can employ cloud services for efficient data storage and processing. Yet, cloud storage services come with the risk of privacy breaches of sensitive data. To cater to this, homomorphic encryption schemes can be used to secure data. 

Wrapping up, The ultimate goal of smart cities is to improve citizens’ quality of life, reduce the cost of living and attain a sustainable environment. However, this revolutionary technology faces some daunting challenges – security and privacy. I’ll discuss these in my upcoming articles.

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