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Surface AI

Machine learning technology that
Autonomously
detects potholes and cracks
by recording vibrations generated by vehicles using just a smartphone.

What is surface AI

Surface AI is a 21th century technology that eliminates the agencies' need to collect international roughness index (IRI) data and to manually locate potholes, cracks and other surface irregularities. Surface AI uses machine learning algorithms to interpret motion (vibrations) data collected from a vast network of motorists who own smart devices or drive smart vehicles as they commute over the roads. The technology operates autonomously and is capable of generating accurate standard IRI data for the entire road network allowing it generate road health reports at lighning speed at very little cost.

Designed for Governments

and road agencies around the world to help maximize efficiency in road maintanance with the power of crowdsourced BigData and artificial intelligence.

Up to 5 level IRI data Data generated in internationally recognized industry standard format

Surface AI generates very detailed and granulated roughness data for road segments as small as 100m for every lane. Data is processed and presented in IRI format and is easily exported to other software programs such as MatLab, Road Doctor for further modeling.

Full road network coverage Our data collection network is crowdsourced.
And huge.

From logistic companies, fleet management systems to everyday drivers using smart devices data flows seamlessly to Surface AI from from various channles. The result is a stable continues flow of data for the entire road network with an unmatched frequency.

Easy to use When it’s simple to do everything, you can do anything.

From logistic companies, fleet management systems to everyday drivers using smart devices data flows seamlessly to Surface AI from from various channles. The result is a stable continues flow of data for the entire road network with an unmatched frequency.

BumpAhead Smart cars can see beyond the line of sight

BumpAhead is a dedicated product for smart cars. The technology allows vehicles to autonomously adjust suspension settings based on location and surface to deliver optimal ride quality and stability for the driver no matter the destination.

Strengths and weaknesses Comparison of data collection processes

Surface AI is the first working scalable data collec on solution that is objective, accurate cost effective, doesn’t require employment of staff or specialized equipment and offers full network coverage and real time data with no agency involvement.

Surface AI

Our disruptive technology solution for road roughness data analytics

Specialized equipment

Designed to collect road roughness data faster and more accurate

Manual road inspection

Used by many road agencies around the world to collect data.

Time & effort
  • No data collection delay.
  • Road surface data is ready to use and update daily for the entire road network.
  • No effort required
  • Reduces data collection times.
  • Requires relatively long time to cover the entire road network.
  • Requires a lot of time & effort for data collection
Scalability
  • Highly scalable at marginal cost
  • Reliant on specialized equipment which highly limits scalability and frequency of data collection
  • Not scaleable. It is cost prohibitive and involves a lot of resources, people, time etc.
Objectivity
  • Objective measurement
  • IRI certified data
  • Objective measurement
  • IRI certified data
  • Subjective since it depends on experience of personnel
Cost
  • Most cost-effective solution
  • No running expenses
  • Very expensive equipment and setup.
  • Substantial running expenses
  • Relatively not expensive.
  • Requires running expenses
Accuracy
  • Very accurate
  • Very accurate
  • Accurate
Data size
  • Full road network coverage even on smaller or hardly accessible roads.
  • Compact and structured data storage.
  • No additional software required for data analysis, reports and archive.
  • Vast amounts of raw data colected and stored depending on capacity of equipment and intensity of road inspections.
  • Requires additional software for data analysis, reports and archive.
  • Low coverage due to phisical limitations.
  • Data is collected on paper or additional software and trained staff is required to manualy input data into digital format
Data handling
  • Not subject to transcription errors.
  • Not subject to equipment failure.
  • Not subject to data handling errors.
  • Excellent quality assurance.
  • Not subject to transcription errors.
  • Subject to equipment failure.
  • Subject to data handling errors.
  • Good quality assurance.
  • Subject to transcription errors.
  • Poor quality assurance.
Staff
  • Does not require data collection staff.
  • Requires at least 1 data analyst to generate reports.
  • Suitable for executive level usage.
  • Suitable for agencies looking to downsize number of employees
  • Requires data collection staff.
  • Requires database administrators.
  • Requires data analysts and specially trained operators to generate reports.
  • Not suitable for executive level usage.
  • Source of employment for inspection staff
  • Requires large staff numbers
  • Requires data input administrators
  • Requires analysis department
Coverage
  • Full road network coverage.
  • Full road width coverage.
  • No action or equipment required to achieve full coverage
  • May cover footprint of data collection vehicle
  • Multiple runs sometimes needed to cover entire road width.
  • Covers entire road width with 1 run
  • Data available only for inspected roads
  • Requires substantial effort for full road network coverage within 1 year
Safety
  • Harmless.
  • Staff not exposed to hazards.
  • Harmless.
  • Staff exposed to relatively low risk of hazards
  • Staff exposed to hazards during data collection sessions.