Video analytics tools are more accessible than ever. Here’s why

Digital Marketers are favoring video marketing more than ever. Definitely, it drives more engagement and has hugely become popular among the consumers. As per recent stats, 80% of online traffic will be video by 2021.

Other than in digital marketing, videos prove to play an important role with every video conference, virtual performances, telehealth appointment, and tele-learning sessions.

The use cases of video are hospital asset tracking, building, workspace & warehouse usage monitoring, thermal imagery for fever detection, methane gas leak monitoring, and counting of livestock.

The role of video has increased since the pandemic. Especially, for big data analytics, which operates and relies completely on video and photographic data.

Advanced technologies like machine learning and artificial intelligence are aiding for improved video analytics solutions. These technologies ameliorate decision-making and more impactful to adhere to best practices and maintain privacy standards.

In order to attain the accuracy of video analytics solutions, marketers and global leaders need to look out for a few challenges.

Challenges with Video Analytics Software

Disconnected Solutions

Video analytic services are distinctive as that of a video management system (VMS). Hence, you need a separate configuration interface, discrete integration efforts, and offer an incompatible user interface that does not go with the rest of the workflow.

No matter the dissimilarity, the integration of third-party solutions will always be a formidable part of any VMS. Notwithstanding the complexity of use, deployment & maintenance of the system, especially for standard applications.

Server Sizes

Since the video analytics software performs from the data gathered from different computing resources, which are increasing as well as their consumption. Hence, the amount of consumption becomes inflated coercion on general-purpose and existing recording servers. Additionally, specialized hardware escalates the complexity of system design.

How Next-generation Video Analytics Solve Problems

The next-gen video analytics in India will streamline the deployment and scalability. The improved version of analytics will reach extensive customers, aiding them intelligent and operational insights to more users than ever before.

Moreover, the video management system will support video analytics applications in the backdrop, which will democratize insights and create metadata. However, the visibility will never be restrained to a particular platform; be it cloud, or camera, or any server. Hence, analytics will be made a standard component of any modern VMS, similar to archiving.

The future visibility of the analytics and its performance could discerning out of VMS through built-in charts, dedicated feature widgets, dashboards, and reports. These visual data will facilitate operators and users to comprehend, classify, and process information faster and better decision-making.

For augmenting the use of video and video analytics, here are a few recommendations

Broadening Business Profile

Experts suggested in order to leverage the assets for multiple applications now as well as in the future, you must have a viable strategy with video. You can begin by identifying a broad range of business cases instead of just one for the video analytics solution. However, investing in video, networks, and bandwidth can be sustainable.

Define a Privacy Policy Before Implementing Video

Well known example, Zoom, a user-friendly platform to connect, but has privacy disintegration. Zoom uses personal information for targeting ads, on or off the platform, or for other business purposes — as per an article published on ConsumerReports.com.

The article was a clear message about refining the application in terms of privacy. The privacy complaints were heightening. The grievance expressed resulted in securing customer content so that it couldn’t be used for advertisement purposes any longer unless the user accorded it.

However, every business use purposes and cases distinctively, still organizations must regulate strict privacy and technology before deploying to withstand user content.

Instigating Automation With Human Checkpoints

Advanced technologies like machine learning and robotic process automation are great tools for enhancing the video and analytics quality and performance accuracy yet could not be stated as foolproof. Additionally, a human judgment must be considered, as a second line of review for drawing conclusions.

To Conclude -

Organizations have become cautious hence are deploying more and more cameras to track and monitor. The new and heightened resources to gather data does inflate pressure on the server but aid with accurate decision-making. However, the privacy of the user content should be an important aspect to be kept in mind while planning to deploy applications.

Rendering the capabilities of advanced technologies such as machine learning amalgamating with strategies to overcome the challenges can brighten up video analytics services and enable the development of applications that were unimaginable even a few years back.