Stopping accidents before they happen key to data project
That's the aim of Justin Strharsky and his technology company Synaptor, which is taking incident logs and other reports generated on sites and analysing them to provide early warnings of risky behaviour or potential mishaps that may lead to injury.
As an indicator of the need for his company's technology, he cited Safe Work Australia statistics showing occupational illness and injuries cost the country $60.6 billion in 2008-09.
Synaptor's critical capability is its capacity to capture and manipulate live data, such as incoming reports of potential hazards like new potholes in roads or workers not wearing appropriate safety gear.
Synaptor analyses these reports and plots the data in real time on an interactive risk map, which is used to predict when and how an individual is most likely to be injured. It then generates an alert.
"One of the things we think is really key to preventing accidents is having the right information at the right time," Mr Strharsky said. "And part of the problem in industry now is that it is always at the wrong time. They are always responding to last month's data."
Mr Strharsky said Synaptor was in discussions with one site that already generated more than 40,000 observations about hazards and employee behaviour each month.
He said the accuracy of the system would improve as more sites provided data. There was also potential to bring in additional site data, such as shift length, swing length, and training records, as well as data from external sources that might have a bearing on safety, such as weather forecasts.
"Safety science has been doing the same thing for the past 60 years and has plateaued in its effectiveness," Mr Strharsky said.
Full story: theage.com.au/it-pro
Frequently Asked Questions about this Article…
The main goal of Synaptor's data project is to reduce accidents on large mining and construction sites by analyzing incident logs and reports to provide early warnings of risky behavior or potential mishaps.
The main goal of Synaptor's data project is to reduce accidents on large mining and construction sites by analyzing incident logs and reports to provide early warnings of risky behavior or potential mishaps.
Synaptor's technology captures and analyzes live data, such as reports of potential hazards, and plots this data on an interactive risk map. This helps predict when and how an individual is most likely to be injured, allowing for timely alerts and preventive measures.
Synaptor's technology captures and analyzes live data from reports of potential hazards, such as potholes or workers not wearing safety gear, and plots this data on an interactive risk map to predict and alert when and how an individual is most likely to be injured.
Real-time data is crucial because it provides the right information at the right time, allowing companies to respond proactively to potential hazards rather than reacting to outdated information.
Real-time data is crucial because it provides the right information at the right time, allowing for proactive measures rather than reacting to outdated data, which is often the case in the industry.
Synaptor analyzes data from incident logs, hazard reports, and employee behavior observations. It also considers additional site data like shift length, training records, and external data such as weather forecasts.
Synaptor's system analyzes data from incident logs, hazard reports, and employee behavior observations. It also considers additional site data like shift length, training records, and external data such as weather forecasts.
The accuracy of Synaptor's system improves as more sites provide data, allowing for better predictions and more effective safety measures.
The accuracy of Synaptor's system improves as more sites provide data, allowing for a more comprehensive analysis and better prediction of potential safety risks.
One major challenge is that companies often rely on outdated data, responding to last month's information rather than having access to real-time insights that can prevent accidents.
One major challenge is that the industry often relies on outdated data, responding to last month's information rather than having access to real-time data that can prevent accidents before they happen.
Synaptor sees potential in incorporating additional site data like shift and swing lengths, training records, and external data such as weather forecasts to enhance safety predictions.
Potential external data sources that could enhance safety predictions include weather forecasts and other environmental factors that might impact site safety.
According to Synaptor, safety science has plateaued because it has been using the same methods for the past 60 years, and there is a need for innovative approaches like real-time data analysis to improve effectiveness.
Synaptor believes traditional safety science has plateaued because it has been using the same methods for the past 60 years, and there is a need for innovative approaches like real-time data analysis to improve effectiveness.
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