In recent years, video analytics has rapidly advanced to keep up with the global reliance on video data. From traditional industries like security to new adopters ranging from retail and hospitality to banking and even healthcare, everyone is clamoring for innovative ways to process their video data and transform it into actionable intelligence. However, because the demands for new capabilities and applications are constantly evolving, the video analytics industry is always innovating solutions to meet the needs of any organization, from small businesses to large multi-site enterprises.
The first step to any innovation starts with evaluating the feedback and needs of our end customers. In doing so, we quickly identified that their input fell into two main categories. They needed to:
In the 15 years since the core BriefCam VIDEO SYNOPSIS technology was developed, BriefCam has evolved into a comprehensive, complete, and AI-driven video analytics solution, offering video search, alerting, and data visualization. While the original BriefCam engine had been built for post-event video search, the technology has expanded to power real-time applications. Our customer feedback forced us to take a hard look at the robust technology we’d built and consider whether its foundation was sufficient for driving performance, accuracy, and speed both for real-time channels and future applications.
The BriefCam team decided that we needed a faster, more powerful way to process video, overcome lags, and significantly increase user situational awareness in real time for our users to realize the full value of their video surveillance investments at a lower TCO. A key factor to lowering TCO was reducing the hardware footprint for the solution: We would need to run more cameras in parallel on the same GPU to save on hardware costs. Although it meant rethinking our engine – the foundational infrastructure of our technology – we decided the only way to effectively solve the critical needs of our customers would be to develop a new engine, based on flexible, AI-based, Linux infrastructure: Our Next-Gen Engine was born.
The most exciting thing about our Linux-based engine is that it represents an entirely different, more modern and flexible approach to development that is based on AI industry standards. This new architecture allows us to quickly add features and flexibly adapt our roadmap to meet the needs of prospects, partners, and customers. Our 2023 M1 Beta partners and early adopters provided critical feedback for maturing the Next Gen Engine and – because of simplified coding and more modular, flexible architecture – we were able to agilely address feedback and quickly improve the robust capabilities of the engine.
One such innovative capability — included in BriefCam 2023 M1 – is Custom ClassifID, which runs only on the Linux engine. With the Custom ClassifID solution, each organization can powerfully define additional object classes for video search, alerting, and intelligence, on top of the ever-expanding set of detected classes available in the BriefCam Video Analytics Platform. Now every environment that is powered by our Next-Gen Engine can leverage BriefCam based on the specific and unique vehicle types or uniformed people required by their business, without sending data off-site or outsourcing classifier network training.
The agility of the Next-Gen Engine is exciting for us here at BriefCam. Our industry is evolving rapidly, and the need for new, reliable, and accurate features and functionality is only increasing. Our new, Linux-based infrastructure empowers us to meet this need and deliver more of what you need to translate video into impact, faster.
Interested in seeing Custom ClassifID in action on our Next-Gen Engine?
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