How Incorporating IoT and Machine Learning Can Reshape the Smart Cities

CIO Review Europe | Wednesday, September 15, 2021

The worldwide population has reached the pinnacle of modernity, characterised by widespread access to cutting-edge technology.

FREMONT, CA: The term smart city refers to a sustainable framework that incorporates information data and communication technology to develop and coordinate behaviours that intelligently support urbanisation.

What are the prerequisites for designing a smart city? Wireless technologies, such as networked gadgets and the cloud, are included in the framework, gaining a sizable part. Without a doubt, the Internet of things (IoT) and machine learning (ML) are favoured technologies for promoting such an idea. These technologies can meet the diverse demands of urbanisation by delivering novel and more intelligent solutions for pleasant living.

The purpose of IoT applications is to handle and analyse real-time data in conjunction with machine learning to aid towns, citizens, and organisations in improving their standard of living.

Smart Cities and IoT                  

To change any city into a smart city, active deployment of IoT technology is required. The internet's worldwide reach is at the heart of IoT applications. Apart from lowering the cost of connectivity, the emergence of smarter gadgets equipped with advanced sensors and Wi-Fi connections helps the Internet of Things' wiser engagement.

AI/ML in Smart Cities

The availability of intelligent machines enabled by Artificial Intelligence (AI) and Machine Learning (ML) has been essential in propelling the notion of smart cities forward. One may now combine advanced computing programmes with human intelligence to build a cyber-physical area that incorporates traffic sensors, video cameras, environmental sensors, and smart metres, among other components. Data collection occurs regularly to generate actionable insights for intelligent city planning.

Incorporating IoT and ML into Smart City Applications

Automated Parking Systems: The combination of IoT with machine learning can support smart parking systems. These systems are designed to identify available parking spaces for vehicles, particularly in public areas.

The existence of an In-Ground vehicle detection sensor enables this because they are embedded within the pavement of various parking spaces. They are responsible for collecting data on the time and duration of vehicle occupancy of space. The data is then uploaded to the cloud, processed and distributed to cars looking for available parking places.

Additionally, machine learning algorithms are used to identify peak hours, which is feasible through a detailed examination of historical trends and real-time data. The availability of an intelligent parking system benefits people by alleviating unnecessary congestion and lowering their fuel expenses.

Public Security: To improve public safety in a city, one can leverage IoT technologies focused on giving real-time information via CCTV cameras and sensing instruments. The complete data obtained by these systems enable the forecasting of criminal activity and the implementation of security measures.

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