Improper Lifting Detection
Improper Lifting Detection
What is improper lifting?
Improper lifting simply means using incorrect methods while moving, carrying, or lifting heavy objects.
Using such methods raises the risks of musculoskeletal disorders and workplace accidents, and in some cases, even fatal accidents like crushing injuries and/or being struck by dropped loads or falls.
Some common examples of improper lifting techniques are:
● Jerking or lifting too quickly
● Bending at the waist instead of the knees
● Lifting loads too far from the body
● Failing to assess the load before lifting
● Twisting the torso while lifting
● Carrying unevenly distributed weight
● Repetitive lifting without adequate rest.
In fast-paced industrial jobsites, these unsafe practices often go unnoticed, especially in large teams or busy shifts. That’s where video analytics becomes crucial.
What makes lifting “improper” in an industrial context?
Improper lifting is not only about bad posture, it is context-specific. A lift that is safe in a warehouse might not be safe on an uneven terrain or near a live machine. By learning from the real-time footage captured by the IP cameras and AI CCTV, video analytics helps identify context-aware lifting risks, while computer vision continuously refines how it defines “unsafe” in dynamic environments.
How does video analytics help in detecting improper lifting?
Using advanced algorithms, video analytics analyses body movements captured by the IP cameras and AI CCTV, to track posture patterns and motion sequences to flag off unsafe lifting in real-time. Powered by computer vision, the system becomes capable of differentiating between safe and unsafe lifting techniques with high accuracy. This enables faster response to prevent both musculoskeletal disorders (MSDs) and life-threatening accidents on the jobsite.
What is the role of AI CCTV and IP Cameras in the process of improper lifting detection?
AI CCTV and IP cameras are crucial elements in the process of improper lifting detection. AI CCTV systems can process footage directly on the device or through connected networks to identify high-risk lifting behaviours without human input. Strategically installed IP cameras, on the other hand, ensure clear, consistent video streams that feed into the video analytics platform. These visuals enable timely alerts and safety reports that help in compliance and monitoring.
Which industries benefit the most from improper lifting detection?
Manual material handling is a common sight in industries like construction, warehousing and logistics, and manufacturing. Video analytics supported by computer vision is ideal for these environments, since they involve repetitive and high-risk lifting.
Article by
Barnali Sharma
Content Writer
Barnali Sharma is a dedicated content contributor for viAct. A university gold medalist with an MBA in Marketing, she crafts compelling narratives, enhances brand engagement, and develops data-driven marketing campaigns. When she’s not busy working her content alchemy, Barnali can be found commanding stages with her public speaking or turning data into stories that actually make sense -because who said analytics can’t have a little creativity?