The advent of 4G and 5G IoT-based connectivity will spur the online migration of smart-city applications, helping generate a significant increase in smart city artificial intelligence (AI) software revenues by 2025, according to a report by Omdia.
The global smart city AI software market is set to increase to $4.9 billion in 2025, up from $673.8 million in 2019, according to projections. Wireless data communication standards will enable smart-city applications to move into the digital realm, where they can capitalise on the latest AI innovations. The growing capabilities of AI are enabling data and insights collected via IoT networks to be monitored, analysed and used to drive autmated smart decisions.
Smart city use cases include surveillance, safety and security, taffic management and building control, and are defined by the collection, management and use of data. In the past, trying to enable disparate systems to work together has been challenging due to the lack of solutions which can handle the heavy processing required tro make sense of data. These challenges are being overcome by leveraging advances in AI and connectivity.
The introduction of 4G and 5G wireless data technologies makes it easier and more cost-effective to collect and manage data, promoting the migration of smart city AI software to digital platforms. AI and associated machine learning technologies allow data to be analysed in greater detail than ever before.
The technology can identify patterns or anomalies within the captured data, which then can be employed for tasks such as automation of actions and decision-making.
Smart city systems can create municipal systems and services that not only operate more efficiently, but also provide significant benefits to workers and visitors. These benefits can come in many forms, including reduced crime, enhanced safety, reduced pollution, managed traffic flows and more efficient provision of services.
One example of how smart cities are leveraging AI is via video analytics, which scans video streams to identify behavioural or situational anomalies.