Page 26 - Security Today, JulyAugust 2023

market are easily understood, video surveillance cameras are also being used by organizations to analyze video footage and extract meaningful insights about sales and operations. By using deep learning algorithms to analyze video footage in real-time, busi- nesses can extract customer behavior data such as foot traffic pat- terns (via heat maps) and product placement effectiveness. By collecting and analyzing this data, organizations can im- prove their operations, optimize store layouts, and improve cus- tomer experiences. For example, retailers can use video analytics to identify popular shopping areas and adjust their store layouts to increase sales. They can also use data to optimize staffing lev- els, reduce queues, and improve inventory management. In healthcare, video analytics can be used to monitor patient and visitor movement and improve the overall patient experience. In trans- portation, video analytics can be used to improve traffic flow and re- duce accidents. And in manufacturing, video analytics can be used to monitor production lines and improve efficiency. The latest AI tools can memorize an entire scene and monitor stock on store shelves or in a warehouse and notify staff when inventory is running low. Overall, AI-based video analytics are becoming increasingly important for organizations looking to harness the power of big data to improve their operations and make data-driven decisions. DEEP LEARNING, IMAGE ENHANCEMENT While deep learning is certainly a boon to analytics, these algo- rithms are also being used to enhance image quality and reduce net- work bandwidth. For example, deep learning can inform the image MNBB Studio/Shutterstock.com “ Deep learning can inform the image processing system in a camera as to which pixels represent a person or vehicle in motion.” processing system in a camera as to which pixels represent a person or vehicle in motion. In this way, a camera can automatically reduce noise and ghosting in low-light conditions around a moving object without impacting static objects and the image background. Similarly, knowing which pixels represent a known object can help the encoder prioritize those pixels over the background im- age. This improves encoding efficiency and saves valuable net- work bandwidth and storage without sacrificing quality. As deep learning technology continues to develop quickly, we’re sure to see even more innovative and powerful applications for security, business, and operational intelligence. The opportunities and applications unlocked by this impressive tool are limited only by our imagination. Any organization should be able to quickly identify ways in which this powerful technology can help stimulate growth and revenue while simultaneously protecting as- sets and individuals. Hiroshi (Huey) Sekiguchi is the chief marketing officer at i-PRO, Inc. 26 JULY/AUGUST 2023 | SECURITY TODAY DEEP LEARNING