Video Analytics Solutions Should Include Streamlined Deployment and Scalability
Fabiola Ruvalcaba, the Commercial Lead for Video Analytics at Genetec, speaks about building a loss prevention strategy, elements to consider when evaluating and deploying video analytics solutions, and more
Why is video analytics important?
For larger retail establishments like shopping malls, bottlenecking is a major issue that can affect customers in vehicles. Roadwork, changes in traffic patterns, and immobilized vehicles can generate sudden delays, or in more extreme cases, risks to health and safety. This is also true for other destination facilities, such as hospitals and airports.
Video analytics can help maintain the flow of vehicles at entry and exit points by alerting personnel of emerging problems. By detecting stopped vehicles in prohibited areas or counting vehicles over a set time, personnel can then be dispatched to address potential issues more rapidly.
The next generation of video analytics solutions will include streamlined deployment and scalability. It will bring video analytics to a wider range of customers, providing intelligence and operational insight to more users than ever before. It will democratize video analytics.
In the future, a VMS will have video analytics permanently running in the background, creating meta-data and providing insights for users. Whether running on a server, in the cloud, or in a camera, this technology will be invisible to the user. Instead of “video analytics” being seen as a separate technology, it will be a standard component of any modern VMS, just like archiving.
How can companies build a loss prevention strategy today?
Digital evidence management systems can help loss prevention and risk management teams become more efficient at handling cases, while also reducing costs. There are four ways companies can benefit from a digital evidence management system (DEMS):
Save time and money handling video requests: The cost of external storage devices and shipping fees can quickly add up. Instead, an investigator could import a video recording from their video management system directly into a digital evidence management system and provide access rights to specific users.
Securely share evidence and data with others: Only authorized users can view evidence within the DEMS. The lead investigator can set specific user permissions within a collaborative investigation management system.
Compile all types of evidence in one place: Companies can collect evidence from many sources, using a central repository to store all information related to a case. This includes media from surveillance systems, mobile phones, or body-worn cameras.
Keep long-term evidence safe to mitigate liability: Whether it is for legal or corporate requirements, businesses can use the investigation management system to store video for the length of their retention guidelines. Admins can pre-define retention periods for certain types of evidence, so the system automatically keeps it for a specified amount of time. Or, users can place a hold on cases and files that must be kept for longer time frames.
What are the elements to consider when evaluating and deploying video analytics solutions?
At first glance, finding the right analytics solutions can seem overwhelming, but the good news is those analytics are now simpler and far more effective than ever. Security platforms that come with built-in analytics are speeding up deployment and delivering accurate results.
A question that’s still frequently asked is: ‘Should I get server-based video analytics or install them on the edge?’
When we refer to edge-based analytics, this means that the camera or encoder is processing the image and creating metadata. In a server-based analytics setup, video streams are sent to and processed on the server, independently from the cameras. Each option is viable and effective, but choosing the best option will depend on your environment.
How can retail stores streamline operations with video analytics?
There are five crucial elements to consider when evaluating and deploying video analytics to increase success:
Define your expectations: Identify the problem to solve first, then, set the right performance expectation, and define metrics for success. Video analytics offer the best insights when deployed as a solution to a problem rather than a solution in search of a problem – the latter is often challenging to evaluate.
Know the best analytics options: Finding the appropriate video analytic for the job will help allocate resources appropriately and limit overestimating results. Consider each analytics’ intended environment of operation and judge how well it matches your scenario. Using video analytics outside of their intended parameters makes performance unpredictable, often to the detriment of your goals.
Don’t set it and forget it: After selecting and deploying a video analytic solution, it is crucial to use the metrics defined to measure performance continuously. Video analytics is not a “set-and-forget” type of technology. High accuracy has traditionally been hard to obtain, especially in open areas with many moving parts and people.
Think beyond analytics: Video analytics usually serves as a trigger point in broader security infrastructure and should link into a centralized, unified system, instead of operating in a silo from which extracting data becomes challenging. The right security system will include event-to-action, alarm management, and map-based monitoring to leverage video analytic data.
Measure ROI: when defining the success conditions of a use case before deployment, establishing the return on investment becomes more straightforward. A good example is the people counting video analytics used to prove compliance with occupancy regulations. This use case’s ROI compares the cost of the video analytic solution against hiring staff to count customers and the cost of any violation of occupancy regulations.
What challenges are retail stores facing when it comes to understanding consumer behaviour?
Decoding customer’s behaviour can be a challenging task, but it’s vital for decision-making and improving the customers’ experience. Using existing cameras and heat maps can help capture the navigational and interactional behaviour of customers. Another challenge is knowing who is in your stores and why. Counting down visitors helps, but, in order to be meaningful, the numbers have to do more.
Gaining an understanding of visitor data along with key performance indicators, retailers can make better, more informed decisions. The use of multi-directional and accurate visitor counting cameras that retail stores already have can help maximize conversions and reduce labour inefficiencies, too.