Chris Kruger | Managing Director | Nashua Kopano | mail me |
Most mid-sized to large organisations in South Africa have made significant investments in IP-based surveillance systems, with a heavy focus on detecting and preventing crime. From warehouses, factory floors and offices to shops and parking lots, organisations have blanketed their properties with digital cameras for security reasons.
Having made these investments in protecting people, information and assets, forward-thinking companies can drive more value from their video surveillance systems by adopting artificial intelligence (AI) or video analytics.
Driving operational excellence
The technology enables companies to turn the vast amounts of video data they collect into insight, in turn helping them to automate business processes and make better business decisions. This technology has advanced in leaps and bounds in recent years. Demand for such solutions is growing at a rapid pace as companies tap into video analytics in industries as diverse as retail, warehousing and logistics, and manufacturing.
The market is forecasted to nearly triple in value from around $7 billion in 2022 to $20 billion in 2023.
Today’s solutions use deep learning and artificial AI to analyse images and videos in real time. The software can detect, recognise, and track people and objects in video footage to identify patterns and anomalies. Cameras can be trained to assess size, shape, speed, and directional information, automating the process of analysing video and extracting valuable insights from the data.
Here are examples of the capabilities of advanced video analytics:
- Detecting whether a person or object has moved or crossed a boundary.
- Identifying whether someone is loitering in a location.
- When used with thermal camera technology, video analytics can raise the alarm about a sudden increase in temperature or when a fire is detected.
- Counting and locating people and automatic number plate detection of vehicles.
- Monitoring the speed of vehicles in a controlled area.
This level of intelligence allows a company to become more proactive about addressing crime on its premises. It turns CCTV from a tool most companies use to analyse crime after it has happened into a solution for preventing it in real time.
But security applications are just the tip of the iceberg. Here are a few other industry use cases:
- In mining and manufacturing, video analytics can be used to detect whether workers are wearing personal protective equipment such as hard hats and gloves as well pipe leak detection.
- Facial recognition can be used to send an alert when someone who doesn’t have authorisation in a controlled area.
- Logistics firms can use video analytics to track parcel movement throughout complicated conveyor systems.
- Factories can harness video analytics for preventive maintenance and product quality control.
- Incidents such as temperature anomalies and fire hazards can be detected and verified in the early stages in industrial settings.
- Retailers can use the technology not only to fight shrinkage and shoplifting, but also to detect low stock, wrong placement, and wrong prices.
- Also in retail, companies can collect and analyse data to identify peak times, traffic patterns, and high occupancy zones. This can help them to optimise product and staff placement as well as improve the flow of customers through their store.
Enhancing better decision-making
Given that most organisations are collecting a wealth of digital video, those that are not tapping into video analytics are missing out on a powerful way to improve return on investment. Such solutions can enable a business to vastly increase efficiencies by reducing the time its people need to spend watching camera feeds and reviewing historical footage.
But even more importantly, video analytics unlocks the value of the vast reserves of operational data most companies are capturing from their surveillance cameras. This empowers them to make better operational strategic decisions, from identifying health and safety compliance issues to driving better customer experiences or detecting bottlenecked processes.