05/11/21 – Frontline Data Systems Features in Government Spend

Frontline Data Systems’ defect detection pilot program in the Australian Capital territory, as well as our upcoming trial with Suez Canberra generates substantial media excitement. 

The Honourable Chris Steele, Minister for Transport and City Services in the ACT invites our own Jonathon Staples to take part in a press release , announcing a $19.5 Million dollar road infrastructure improvement program. 

Nine Canberra Coverage:

ABC News Canberra Coverage:

Canberra Times Coverage:

01/11/21 – East Gippsland to Trial Magpeye’s Accuracy

The East Gippsland Shire will conduct a trial of Frontline Data System’s solution to improving the accuracy of road condition assessments over the next three days. 

The trial will be used to assess the accuracy of our perceptual sensory system by comparing it to the results of a human default detection system. 

Frontline Data Systems will assist East Gippsland Shire in making an assessment of whether Magpeye can support East Gippsland Shire in providing the best road health possible for it 47,725 residents.

01/06/21-IPWEA & Local Government NSW Concludes Trial of Frontline Data System

The Institute of Public Works Engineering Australasia & Local Government NSW has concluded their report: Automated Detection of Road Defects Evaluation, commissioned to “identify a range of new and emerging opportunities in supporting developments for artificial intelligence to identify road defects.” 

The capacity of Frontline Data System, & seven other automated road defect detection systems were tested across 295.8km of urban, rural and unsealed roads in Blayney Shire, Canterbury Bankstown, Central Coast, Georges River council.

The report’s findings were supportive of both Frontline Data’s System’s ability to accurately & efficiently detect road defects and the transition from manual to automated road defect detection systems more broadly. The report concluded: 

“Frontline Data Systems offers a tailored model that can detect most ordinary road surface defects at human-level accuracy and can be trained to work effectively on dashcam footage of any acceptable nature.”

“It [Frontline Data Systems] was able to detect cracking in 88% of its surveyed sections where another system also identified a crack, indicating strong potential for crack detection.” 

“The project has proven the value of artificial intelligence for asset inventory, asset condition assessments and the establishment of maintenance programs for roads and transport assets. The outcomes are applicable to any movements and place assets, including roads, footpaths, parks and other outdoor spaces.”

01/03/21 – VicRoads and Frontline Data System

VicRoads has conducted a pilot program with Frontline Data Systems “to establish the viability of Artificial Intelligence in conducting road surface assessments”. It found:

“Whenever the human surveyor detected a defect on a SIR segment (see appendix A) the AI surveyor would detect that same defect on the same segment 75% of the time.”

“In some cases the AI surveyor detected defects that the human surveyor did not. Visual analysis suggests that many of these defects were identified correctly.”

“The graphs below indicate all instances where the AI assessor’s predictions agreed with those of the human assessor (left) and all instances where the human assessor reported defects that the AI assessor did not (right).”