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Unlocking the Power of Large Visual Models in Video Analytics: Opportunities, Challenges, and the Critical Role of On-Premise Deployment
Implementing AI video analytics to enhance safety across various industries presents notable challenges. Systems must align with OSHA compliance, accurately detecting and responding to safety breaches such as improper equipment use or unsafe behaviours. Additionally, AI must reliably distinguish between normal activities and genuine safety threats, such as falls, to effectively trigger emergency stops in machinery during incidents. This requires sophisticated AI technology capable of real-time, accurate assessments and seamless integration with existing industrial operations. Ensuring both precision and reliability while minimising false alarms is crucial for improving safety measures and operational efficiency in diverse industrial settings. These challenges demand advanced AI solutions tailored to specific environmental conditions.
IntelexVision’s iSentry, an AI-powered platform has been successfully deployed across various industries worldwide for detecting unusual behaviors. This system is designed to enhance OSHA compliance and safety measures, protecting people, property, and assets in critical infrastructure settings.
Hospital
Airports
Shopping malls
University campuses
Borders
Solar farms
Pipelines
Implementing effective safety measures across various industries often faces challenges such as ensuring PPE compliance, preventing falls, monitoring the proper use of tools and machinery, and controlling access to protected zones. In many environments, even a slight deviation in protocol can lead to significant risks, and traditional monitoring methods may fail to catch every infraction or may only react after an incident occurs. Additionally, coordinating a rapid response to accidents and emergencies like smoke and fire remains a critical challenge. Integrating AI video analytics into safety protocols offers a proactive and real-time solution to these issues. By continuously analysing video data, AI can instantly identify non-compliance with PPE usage, detect unusual postures that may indicate a fall, recognise unsafe handling of tools and machinery, and alert breaches in protected zones. This real-time monitoring allows for immediate corrective actions, significantly reducing the risk of accidents and enhancing overall safety. Moreover, AI-driven systems can automate incident responses, ensuring that emergencies such as smoke and fire are managed swiftly and effectively, further safeguarding workers and assets. This technological approach not only boosts compliance rates but also transforms safety management into a dynamic, data-driven process, optimising the deployment of safety resources and reducing downtime due to safety breaches.
iSentry from IntelexVision can address several critical use cases across industries, enhancing safety and operational efficiency. Here are some specific applications:
Perimeter Security: iSentry ccan monitor the perimeter of the facilities, detecting and alerting security personnel to any unauthorised access or potential intrusions in real-time. This helps prevent breaches and protect valuable assets.
Smoke and fire detection: iSentry can help protect the facilities by providing real-time alerts for early detection of potential fires, enabling rapid response and preventing catastrophic damage.
Safety Monitoring: iSentry can monitor operational areas for safety compliance, detecting unsafe behaviours or conditions such as personnel not wearing protective equipment or entering hazardous zones. This helps maintain high safety standards and prevent accidents. Detection of falls or slips is also of critical importance.
Incident Investigation: The system can record and store video footage, enabling detailed analysis of incidents such as theft, vandalism, or equipment malfunction. This facilitates thorough investigations and supports the resolution of security and safety, or operational issues.
Asset Protection: iSentry can track the movement of valuable equipment and materials within the facility, ensuring that they are not tampered with or stolen. This enhances asset management and reduces losses.
iSentry is an Artificial Intelligence-powered video analysis platform. It can be installed on new systems as well as the vast majority of existing CCTV systems.
Equipped with the latest Artificial Intelligence (AI) and Neural Networks based Machine Learning algorithms, iSentry quickly learns what is normal from an individual CCTV camera feed, so that it can then detect the abnormal. It can be deployed in systems from just a few cameras up to thousands of cameras.
After a norm is established for a particular scene, the system will then create alerts based on exceptions or ‘events of interest.’ iSentry then classifies each event upon detection using Deep Learning tools and a logic engine. This provides instant situational context to control room operators so that they can better understand what they are being shown, allowing them to respond appropriately.
iSentry can, for example, recognise that five or six men huddled around a valve for a prolonged period may be an event of interest, and it can differentiate and understand that staff are performing necessary maintenance.
iSentry detects loitering, directional violation, unusual objects entering a scene, running, violence, tailgating, smoke and fire, major leakages, removed or introduced static objects, people climbing walls, entering a perimeter or area,
or graffiti/signs painting. iSentry can also carry out pose analysis, (whether someone is standing, sitting, lying on the ground or has fallen) and many other abnormal situations.
Its Deep Learning engine recognises multiple classes of objects even at difficult angles. Additional capabilities have recently been added such as the ability to monitor for Health & Safety compliance, for example, the wearing of hard hats, high visibility jackets, eye protection glasses, face shields or facemasks for COVID compliance. Additional context could be added by cutting-edge
Generative AI Aurora, first in class LVM model in the industry.
iSentry´s powerful Logic Engine can largely and autonomously fulfil the function of a video surveillance operator. More than 80% of the time it will be capable of reaching a correct decision regarding an event of interest, based on the number and combination of object types that trigger an alert, the time of day and object size, or even the likelihood of accurate classification.
Any incident that iSentry cannot confidently classify automatically or determine through the rules engine whether to dismiss or alarm is then transferred to a human operator for further investigation and decision-making. iSentry empowers control room operators to solely focus on those decisions at which humans excel. iSentry also enables control rooms to function effectively with far fewer operators, as massive quantities of video can be meaningfully and accurately monitored, and processed by the platform.
iSentry’s AI video analytics technology enhances safety across various industry verticals by focusing on specific, contextual use cases beyond simple object classification. For instance, in construction settings, iSentry can confirm that individuals working at height are equipped with the necessary personal protective equipment (PPE), such as harnesses and lifelines, ensuring compliance with safety standards. It can also detect vehicles engaging in unsafe driving behaviours or not maintaining safe horizontal positions, crucial for preventing accidents in both industrial and urban environments.
Furthermore, there are endless use cases possible. iSentry’s capabilities extend to monitoring load distribution on trailers to prevent transport accidents due to unbalanced loads. The system can identify unauthorised access to restricted areas and alert security personnel when individuals or vehicles approach dangerously close to hazardous zones. By applying AI to these specific scenarios, iSentry significantly improves safety protocols, reduces risk, and enhances monitoring efficiency across various operational landscapes
There were 3,286 fatal accidents at work in the EU in 2022, a decrease of 61 deaths compared with the year before. In 2022, close to a quarter (22.9%) of all fatal accidents at work in the EU took place in the construction sector. In 2022, more than half (53.0%) of all accidents at work in the EU caused wounds and superficial injuries, or dislocations, sprains and strains.
IPrivate industry employers reported 2.6 million nonfatal workplace injuries and illnesses in 2023, down 8.4 percent from 2022. There were 946,500 nonfatal injuries and illnesses involving days away from work (DAFW) in 2023, 20.1 percent lower than in 2022. These represented 62.0 percent of cases involving days away from work, job restriction, or transfer (DART).
iSentry is a smart, non-invasive security platform delivering high detection rates that does not use facial recognition technology nor any Personal Identifiable Information
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