CLOUD CAMERA MARKET ANALYSIS

Cloud Camera MarketSize and Trends

The global cloud camera market size is estimated to be valued at US$ 12.8 million in 2023 and is expected to reach US$ 32.2 million by 2030, growing at a compound annual growth rate (CAGR) of 14.1% from 2023 to 2030.

Market Trends:

• AI-Powered Video Analytics: Cloud cameras are increasingly integrating Artificial Intelligence (AI)-powered video analytics to provide more intelligent and proactive surveillance. AI algorithms can recognize objects, detect anomalies, and categorize events, enabling users to receive more relevant and accurate alerts. This trend enhances security effectiveness and provides valuable insights for businesses and homeowners.

For instance: In 2020, a report from the United Nations Office on Drugs and Crime highlighted that the use of Artificial Intelligence (AI)-powered video monitoring in Georgia significantly expedited the resolution of criminal cases. This technology facilitated a rapid matching of footage with a database of known suspects, leading to the swift resolution of 85% of cases.

• Edge Computing Integration: Edge computing, which involves processing data closer to the data source (in this case, the camera), is gaining traction in the cloud camera market. By performing data processing and analysis at the camera level, edge computing reduces latency and enables faster responses to events, critical for real-time security scenarios.

For instance: According to information provided by the UK Home Office for the period between 2020 and 2021, more than 80% of newly installed public surveillance cameras in major city centers and transportation hubs employed edge-integrated cloud camera systems.

Cloud Camera Market Trends:

• AI-Powered Video Analytics: Cloud cameras are increasingly integrating Artificial Intelligence (AI)-powered video analytics to provide more intelligent and proactive surveillance. AI algorithms can recognize objects, detect anomalies, and categorize events, enabling users to receive more relevant and accurate alerts. This trend enhances security effectiveness and provides valuable insights for businesses and homeowners.

For instance: In 2020, a report from the United Nations Office on Drugs and Crime highlighted that the use of Artificial Intelligence (AI)-powered video monitoring in Georgia significantly expedited the resolution of criminal cases. This technology facilitated a rapid matching of footage with a database of known suspects, leading to the swift resolution of 85% of cases.

• Edge Computing Integration: Edge computing, which involves processing data closer to the data source (in this case, the camera), is gaining traction in the cloud camera market. By performing data processing and analysis at the camera level, edge computing reduces latency and enables faster responses to events, critical for real-time security scenarios.

For instance: According to information provided by the UK Home Office for the period between 2020 and 2021, more than 80% of newly installed public surveillance cameras in major city centers and transportation hubs employed edge-integrated cloud camera systems.