Big Data and Artificial Intelligence for Road Infrastructure Sustainability

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Big Data and Artificial Intelligence for Road Infrastructure Sustainability
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Big Data and Artificial Intelligence
Team Organizations RoadBotics Inc.
Team Leaders Nikhil Ranga
Participating Municipalities Cumberland MD
Status Implemented
Document None

Description

Provide an efficient and effective solution using artificial intelligence and smartphones to monitor and maintain roadway infrastructure with a data-driven approach. Projects at RoadBotics aim to provide better data and identify which roads are failing and which roads need early intervention in order to avoid total reconstruction.

Challenges

Manual road inspection method is subjective, time-consuming, and labor-intensive. An alternative - sensor retrofitted vans provide granular information, but they are very expensive, and therefore infrequent.

Solutions

With artificial intelligence and smartphones, RoadBotics automates the process for governments, lowers the cost, saves time, and provides a powerful library of objective visual data to help prioritize pavement maintenance needs.

Major Requirements

  • RoadBotics receives a map of the entire road network that the city maintains.
  • RoadBotics Operations Technicians drive the entire road network to collect data using smartphones mounted on the windshield of regular passenger vehicles.
  • Collected data of road images are analyzed using image processing and artificial intelligence to rate the road conditions based on damage
  • The evaluated roads are automatically categorized into 5 levels based on severity of damage.
  • Municipality receives access to RoadWay, an online map, to view the road conditions of its entire road network along with downloadable files that are compatible with existing GIS systems.

Performance Targets

Key Performance Indicators (KPIs) Measurement Methods
  • Reduction of road assessment time
  • Reduction of costs in entire road inspection process

Reduction in submission of road reports

Standards, Replicability, Scalability, and Sustainability

There is a desperate need to improve the world’s civil infrastructure, and it starts with how they are monitored and maintained. RoadBotics’ use of smartphones to collect data and artificial intelligence to assess the collected road images is a readily available process that can be scaled and replicated across the world. The inexpensive and frequent assessment would lead to improved roads, sidewalks, and bridges, far lower maintenance costs, and less material waste.

Cybersecurity and Privacy

  • Because RoadBotics has been aware from early on that the data collection process has the risk of incidental capture of PII [personally identifying information], the analytics process is designed to remove such data preemptively. At the moment, RoadBotics irreversibly obscure license plates and faces, but could rapidly implement other mechanisms for PII protection.
  • RoadBotics uses a first class cloud security provider (Google Cloud Firebase) for secure authentication of our systems, and never capture online financial data from any municipalities.

Impacts

  • Better road maintenance leads to improvement in surface conditions, therefore, improving safety.
  • Better roads reduce congestion
  • Better roads attract more businesses
  • Improves inter-departmental communication

Demonstration/Deployment

The demo will show how Cumberland, MD uses the RoadBotics data to evaluate the conditions of their roads, prioritize maintenance needs, and implement maintenance plans in their paving program to gradually improve the condition of their roads.