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Integration of Analytics and Machine Learning into Computer Aided Dispatch to Drive Market Growth – Fact.MR Analysis

The computer aided dispatch market is scheduled to grow at a CAGR of 11.2% during the forecast period ranging from 2022-2032, reaching US$ 5.95 Bn, according to a recently revamped report published by Fact.MR. Growth is attributed to extensive uptake for monitoring security across local, regional and global levels.

From 2017 to 2021, demand for computer aided dispatch systems and software accelerated at a CAGR of 10%. During the COVID-19 pandemic, enterprises and healthcare providers alike extensively deployed computer aided dispatch solutions to monitor progress of employees and patients.

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Future market demand is expected to surge even further, as several enterprises shift to the virtual landscape. This will necessitate increased deployment of safety monitoring software, along with advanced computer aided analytical tools.

Key Takeaways from the Market Study

Rising security vulnerabilities, both in the conventional and virtual sense, is prompting countries and industries to develop extensive protection networks to secure sensitive information, widening scope for deploying computer aided dispatch solutions,” comments a Fact.MR analyst.

What are the Factors Driving the Demand for Computer Aided Dispatch Software?

Extensive Reliance on the Internet of Things (IoT) Augmenting Adoption

The computer-aided dispatch solutions continue to gain ground in public transport, safety, reporting, and emergencies services verticals. As network speeds increase and become more economical, computer aided dispatch (CAD) technology will expand, and systems will have the ability to share rich data including images and videos, with first responders enroute to an incident to provide information for enhanced situational.

The development of the IoT continues to provide a strong infrastructure required for the growth of the computer aided dispatch market. Snowballing connectivity between objects has empowered effective detection, monitoring and management of resources and human life.

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