What do you do if your video analytics capabilities need a boost from innovation?

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In the fast-evolving realm of video technology, staying ahead in video analytics is crucial for maintaining a competitive edge. Whether you're managing security footage, analyzing consumer behavior, or developing content, the pressure to deliver accurate and insightful data is immense. But what happens when your current video analytics system isn't cutting it anymore? Innovation is the key to upgrading your capabilities, ensuring that your analyses remain top-notch and your insights stay sharp. In this article, you'll discover practical steps to boost your video analytics through innovation, keeping you at the forefront of the video technology curve.

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1 Upgrade Tools

To enhance your video analytics, consider upgrading your software and hardware tools. Newer versions often come with improved algorithms that can detect and analyze video content more accurately. Look for tools that offer advanced features such as facial recognition, object tracking, and behavior analysis. By investing in the latest technology, you'll be able to process and analyze video data more efficiently, leading to better decision-making and improved outcomes for your projects.

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Ollencio D'Souza

Managing Director at TechnologyCare
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Start with what you consider as "Video Analytics". IEC62676-6 is an emerging standard on video analytics where the core capability of a video analytics system is a system that can "classify objects". An object is anything that can be recognised consistently and accurately like a person, car, dog, etc.. Once an object is classified you consider "behaviour"! So a capable video analytic system is one that can tag an object and document how it behaves. A good video analytic system is one that has the ability to define and check against behaviours such as loitering, slip and fall, person down, direction of travel, speed, etc. An excellent video analytic system is one that can do all the above and produce data defining the activity.

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Kirk Armstrong

National Account Manager at OMNILERT
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Video Analytics are "ever changing" and evolving. First compare how your "analytics" stack up & what your developmental goals are? Collaboration can also be key as you progress. Who can you partner with to contribute to their developmental research & gain collaborative partnerships with? What algorithms work best for your analytics and how can machine learning enhance those possibilities? This all can help you on many of your goals for the analytics you specialize in. Lastly, keep the integration & the quality of the data pristine...in short...the better you plug in...the better you get out! Do not just limit your data from cameras either...find additional sources & capitalize on that as well!

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2 Embrace AI

Artificial Intelligence (AI) is revolutionizing video analytics by providing deeper insights and automating complex processes. Integrating AI into your system allows for real-time analysis, anomaly detection, and predictive analytics, which can be game-changers for your operations. Start by identifying areas where AI can have the most impact, such as improving accuracy or speeding up data processing, and work towards implementing AI-driven solutions that cater to those needs.

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Adam D.

Innovative Problem Solver | MD at Datnexa | Pioneering Data Science & AI for a Better Tomorrow | Driving Purpose-Driven Technology Solutions
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So AI smart analytics can transform hours of video footage into data. This enables analysis of large amounts of information and identify trends and patterns more quickly and accurately. Deep learning techniques, such as convolutional neural networks, are particularly useful in this regard, AND SUPER COOL, allowing systems to automatically detect objects and events with high precision. Edge computing, where data processing occurs on the device rather than a central server is probabtthe future as it improves performance and is cheaper.

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3 Data Management

Effective data management is essential for maximizing the potential of your video analytics. Organize your video data storage to ensure quick and easy access for analysis. Implementing a robust data management system helps in handling large volumes of video content and enhances the efficiency of your analytics processes. Consider using cloud-based solutions for scalability and collaboration, allowing you to manage and analyze video data from anywhere.

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4 Training Programs

Your team's expertise is as important as the technology you use. Invest in training programs that focus on the latest trends and techniques in video analytics. Ensure that your team is well-versed in the software tools and AI applications that you plan to use. Continuous learning will keep your team's skills sharp and ready to tackle the challenges that come with complex video analytics tasks.

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5 Collaborative Efforts

Collaboration can lead to innovative solutions that you might not discover on your own. Engage with industry experts, attend conferences, and participate in forums to exchange ideas and learn about emerging trends in video analytics. Building a network of professionals can provide valuable insights and potentially lead to partnerships that will enhance your video analytics capabilities through shared knowledge and resources.

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6 Continuous Testing

Finally, innovation requires a willingness to experiment and learn from trial and error. Implement continuous testing of new methods and technologies within your video analytics framework. By regularly evaluating performance and making adjustments as needed, you'll stay ahead of the curve and ensure that your video analytics system is always operating at its best.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What do you do if your video analytics capabilities need a boost from innovation?

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1 Upgrade Tools

2 Embrace AI

3 Data Management

4 Training Programs

5 Collaborative Efforts

6 Continuous Testing

7 Here’s what else to consider

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