Smart City Playbook

Transport & Mobility

Usecases

Predictive Road Maintenance

The predictive road maintenance initiative aims at empowering the development of a safe, responsive and reliable transport network. By adopting special measurement vehicles equipped with high-resolution sensors and control units connected to a cloud, these vehicles can capture the road condition (e.g., driving lanes on highways across the city). Such sensors scan the road surface to predict and generate insights on roads that are prone to be deteriorated and require maintenance due to previous accidents causing damage and road anomalies. The initiative would allow Al Madinah city to be proactive to ensure more pleasant and safer journeys for residents and visitors.

KEY

CHALLENGES

Authorities are unable to effectively manage and accommodate the seasonal and continual pedestrian and vehicle traffic across the city

Road accidents and related fatality rates are still on the rise

KEY EXPECTED BENEFITS

Cost Efficient Detection

Unnecessary intervention costs will be reduced since road workers can remotely connect and analyze road issues to provide solutions and maintenance ahead of time

Safer Roads

City authorities will be able to respond faster to accidents

ALIGNMENT TO SMART CITY OBJECTIVES

Responsive

TARGET USERS

Mobility Authorities

Auxiliary Mobility Services

Mobility Designers

Technicians

USE CASE

JOURNEY

Nazim is a data scientist working for a private road maintenance company in Al Madinah city. The company has been planning on developing a predictive road maintenance model to support a safe, responsive and reliable transport network.

Nazim and his team have designed for high-resolution sensors which can be configured on road vehicles. These sensors are connected to a control unit connected to the cloud, enabling vehicles to capture the condition of roads across the city and report back to the unit.

Once sensors scan the road surface, they collect data on road condition, and send it to the control unit which analyzes historical patterns with weather conditions and external impacting factors to predict and generate insights on the roads most prone to deterioration. These road are then prioritized, and necessary works are conducted to prevent future damages and maintain a safe and sustainable road infrastructure.

POTENTIAL SERVICE FEATURES

Detection of road anomalies

AI/ML-driven surface check and solution identification

Alert and navigation system

Technician visit planning

Automated maintenance check-in

Monthly report generation

KEY TOUCH POINTS

Mobile App

Website

Drones

Technicians

Robotics

Simulations

CCTV Cams

Implementation
Timeline

Within 6 months

12 – 18 months

Over 24 months

Technology Commercial Viability

Currently commercialized

1 – 3 years to commercialize

5+ years to
commercialize

Regulatory Conduciveness

No New Policies and
Standards

Some Policies &
Standards to be
Introduced

Complex Policies to be
Introduced

Investment Requirement

Low

Medium

High

Use Case Ownership

Government Driven

Piloted by Gov. & Transitioned to Private Sector

Private Sector

Startups & Entrepreneurs

IMPLEMENTATION CONSIDERATIONS

Consolidation of public and private parking inventories

Network and internet connectivity in indoor and underground spaces

Potential installation and integration of supporting infrastructure for outdoor parking spots

POTENTIAL TECHNOLOGY SOLUTIONS

IN THE MARKET

Transport & Mobility

Use Cases

Smart End-to-End Parking Systems

Real-Time Responsive City Transport Infrastructure “Mubasher”

Predictive Road Maintenance

Car-Pooling and Sharing City Platform “Wasilni”

Assistive Technologies for Public Transportation

Driving School
of the Future

Urban Micro-Mobility Solutions Platform “Jawlat Al Madinah”

Move in Al Madinah Companion App

City EV Digital Hub