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Seamless Safety: Anti-Collision Monitoring Systems in Modern Worksites


Anti-Collision Monitoring Systems, Collision Detection System
Seamless Safety: Anti-Collision Monitoring Systems in Modern Worksites

Collisions at worksites represent a substantial hazard that can be unexpected, leading to severe injuries, costly damages, and operational disruptions. Industries across the globe have battled with these challenges since inception, often relying on traditional safety measures that fall short of ensuring comprehensive protection.

 

According to the IPAF Global Safety Report, being hit by vehicles or machines at worksites remained at the top 5 list of causes of accidents from 2021 to 2023. A substantial shift can be seen in the construction sector where the number of fatalities increased 125% from the year 2022 to 2023.

 

While this is a look into one sector, there are concerning cases found around other industries such as manufacturing, logistics, oil & gas, and mining. Let’s dive into the most common forms of collisions that govern around the worksites in these industries.


Navigating Common Collision Risks Across Industries

Common Collision Risks, Common Collision at Worksites
Navigating Common Collision Risks Across Industries



Collisions at worksites can occur in various forms, each presenting unique hazards and necessitating specific preventive measures. Understanding these risks is pivotal to effective safety management.


Human-Machine Collision


Human-machine collisions are a critical concern in industries where workers operate in close proximity to heavy machinery. In a sector like construction and manufacturing, this scenario is very common.

 

Some of the repeatedly occurring instances involve –

 

  • Forklift and Pedestrian Collision

  • Conveyor Belt and Inspector Collision

  • Dump Truck and Laborer Collision

  • Overhead Crane and Maintenance Worker Collision


The common form of monitoring applicable in such situation relies solely on the hands of bystander supervision and the ability to make the right judgment of the situation. This response can be heavily impacted by the supervisor's ideation of the proximity between the machines and the workers. Being humans, this judgment can also vary based on their fatigue levels from time to time.


Machine-Machine Collision


Machine-machine collisions occur when two or more pieces of equipment come into contact, often due to operator error, poor visibility, or system malfunctions. In any worksite from construction, manufacturing to oil & gas and mining, the involvement of machines are crucial but it can lead to serious collisions leading up to equipment damage, operational downtime, and financial losses.

 

Here are some real-life worksite instances leading to machine-machine collisions-

 

  • Tower Crane and Mobile Crane Collision

  • Haul Truck and Loader Collision

  • Drill Rig and Crane Collision

  • Pallet Truck and Conveyor System Collision

 

The collision effect of machines is dependent on the speed and deceleration values involved which must be kept under loop when monitoring. As these are mobile plants at work, human monitoring system might take longer instances to realise it and crash prevention mechanisms might become critical.


Machine-Object Collision


Collisions between machines and stationary objects, such as structures, barriers, or other equipment, can cause substantial damage and disrupt workflows. These collisions are often due to blind spots or lapses in manual monitoring.

 

Here are possible scenarios across industries where the accurate detection are required to avoid Machine-Object Collision:

 

  • Crane and Overhead Power Line Collision

  • Dump Truck and Temporary Fence Collision

  • Truck and Loading Ramp Collision

  • Drill Rig and Pipeline Collision

  • Maintenance Vehicle and Control Panel Collision

 

The distance calculation when placing machines and objects at the same perimeter of activities is critical. The movement detection and revising of the optimum distance between them requires to be swift and automated.

 

This is where the use of AI-powered safety monitoring can position itself better than a manual monitoring process. The role of AI is profound in all the three major forms of collision found across different sectors.

 

Here are the benefits of deploying an Anti-Collision Detection System at work.


Efficient Safety Solutions: AI-Powered Anti-Collision Monitoring System

Anti-Collision Monitoring System, Collision Detection System
AI-Powered Anti-Collision Monitoring System



The critical part in collision detection is an automated and uninterrupted method of monitoring that can work beyond human intervention. The integration of AI in collision detection systems overcomes this necessity and enables worksite safety, offering several key advantages over traditional methods:


Precision in Incident Prevention


AI-powered surveillance systems leverage advanced sensors, GPS, and cameras to monitor the worksite with high accuracy. The sensors can cover a long range and the algorithms help to translate the processed data within a fraction of seconds. This precision enables the early detection of potential collision risks, allowing for timely interventions that prevent accidents.


Real-Time Threat Identification


The major highlight of AI-processed data is its utilisation in real-time. It promotes identifying and analyzing threats as they arise. This include -

 

  1. Forward collision warning

  2. Detecting pedestrians

  3. Unusual Traffic Congestions

  4. Warning on blind spots

 

The all-round approach helps workers and machine operators detect potential collisions at the right time.


Automated Risk Mitigation


AI systems can automate safety protocols, such as slowing down or stopping machinery when a potential collision is detected. The inclusion of assistance programs such as automatic emergency braking, using stability control systems for adjustments, or providing parking assistance makes risk mitigation automated to a precise level.


Advanced Safety Analytics


AI-powered systems collect and analyze vast amounts of data from the worksite, providing insights into patterns and trends related to collisions. The deep learning methods engraved in the anti-collision monitoring systems help to hold data for longer durations and process every inch of detail around together to predict future safety management tactics.


Efficient Operational Oversight


The comprehensive monitoring capabilities of AI systems enable better oversight of worksite operations. By providing a clear and continuous view of the environment, these systems help ensure that safety protocols are adhered to, and potential hazards are promptly addressed. Efficient operational oversight also includes the ability to generate detailed reports and logs for compliance and review.


Innovation in Action: viAct's AI-Powered Anti-Collision Monitoring System

viAct Anti-Collision Detection System embodies all the advantages discussed above while featuring some of its unique inputs to the scenario.


1. Scenario-Based Analysis


viAct’s system conducts detailed scenario-based analyses, considering various operational contexts to identify potential collision risks. It can be achieved using 4 easy steps-


Step 1 – Install the Existing Cameras on the Vehicles or Machines


Use the existing cameras on site having a resolution of 2 MP or more and place them around the vehicles or machines including cranes, excavators, forklifts, or any elevated platform.

 

Step 2 – Mark the Danger Zones

 

Define or draw the areas that are to be marked as a danger zone when these machines are at work.

 

Step 3- Get Automated Alerts on Collision Risks

 

As soon as any worker, machine, or vehicle is identified as either moving or standing still within the danger zone, the computer vision technology induced in the system detects it and sends instant alerts to concerned safety officers, supervisors, and the involved workers on the premises.

 

Step 4- Use the Recorded Data for Safety Management

 

The records from every incident or the near misses are stored in the intuitive dashboard viHUB which can be accessed at any point in time. It collects and analyzes data from multiple sources, providing detailed insights into safety trends and collision patterns.


These four steps are the basis for getting an uninterrupted AI-powered Anti-collision detection system across all sectors.


2. Integration of Advanced AI Tools


viAct utilizes advanced AI technologies, including computer vision and Generative AI, to provide precise and reliable collision detection. Here is a look into the different tools based on AI to strengthen its collision prevention system.


AI- Powered Tool

Description

Anti-Collision Detection Using

Coverage

AI-powered video analytics provisioned mobile device

Operator Distraction Detection

 

Danger Zone Detection

 

Lifting Object Recognition

 

Intrusion Detection

5M horizontal coverage

 

6M vertical coverage

 

900 downward visualisation

Mobile AI monitoring device operating without internet or electricity

50 Hours Battery Capacity

 

Plug & Play

 

Wireless Alert System

Module for complex crane operations across sectors

Danger Zone Detection

 

Lifting Object Recognition

 

Intrusion Detection

Danger zone detection within 7M radius from the crane hook

 

Detects any obstacle within 3M of the loading and unloading area. 

 

The Danger Zone AI Alert System (DZAAS) is responsible for generating the alert system in case of all the modules. It utilises both light and sound alarms that tick within a second of risk detection. It notifies via SMSs/Emails and records the instance in real time for analysis in the future.

 

viAct’s innovative solutions exemplify the transformative potential of AI in creating safer, more productive worksites. As the industry evolves, embracing these advanced safety systems will be crucial in setting new standards for workplace safety and operational excellence.


 

Captivated by viAct’s Anti-Collision Monitoring System?

 

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