Mobile Data Collection Unlocks Transport Efficiency: How Data is Redefining Infrastructure

Key Takeaways

 

1. Transport and infrastructure are the essential systems that facilitate the movement of people and goods and support societal function.
2. The transport sector is a crucial sector that involves road networks, aviation, rail systems, marine transit, and ports, which are the lifeblood of global trade.
3. Despite its global prominence, the sector faces acute challenges with urban areas struggling with traffic congestion, leading to delays, increased fuel consumption, and pollution.
4. Sensors, cameras, and mobile data collection tools can help address these challenges by providing accurate, real-time insights to manage transportation.
5. This article describes real-world examples of how data has streamlined transport sectors across the globe.
6. We also explain in detail how mobile data collection works, from collection, management, analysis, visualization, and reporting.

 

 

Also read: Mobile Data Collection in Education: Transformative Real-World Case Studies

 

 

What is Mobile Data Collection and How Does it Work?

Mobile data collection is the process of capturing information using mobile devices like smartphones and tablets, often through specialized apps, to streamline data capture, storage, and transmission.

It enhances transportation and infrastructure through real-time monitoring, analysis, and optimization.

Transport and infrastructure professionals are increasingly adopting mobile data collection tools, such as:

 

1. Civil engineers
2. Transportation planners
3. Urban planners
4. Infrastructure inspectors
5. Public transportation officials
6. Construction managers

 

While mobile data collection can take time to master, expert training greatly speeds up the learning process.

In-person training, consultancy, or self-paced mobile data collection courses significantly enhance infrastructure professionals’ capacity to collect data through digital tools and ensure real-time access to actionable insights.

 

 

GPS mobile data collection provides location-based information assisting road users with real-time navigational assistance. Picture/Courtesy

 

How Mobile Data Collection Works

The following is a step-by-step breakdown of how mobile data collection works, along with some of the tools used at each stage of the process:

 

1. Designing Flexible and Dynamic Digital Forms

Survey authoring tools allow users to create customized digital forms capable of handling various data types, including text, GPS coordinates, barcodes, images, and voice recordings.

These tools assist in designing, testing, and deploying digital forms efficiently.

Some mobile tools used in form design include:

 

1. XLSForms – Excel-based form design standard used by ODK, KoboToolbox, and CommCare.
2. ODK Build – Drag-and-drop form designer for ODK users.
3. Kobo Form Builder – Simplified visual form creator for KoboToolbox.
4. SurveyCTO Designer – Enterprise-grade form-building with conditional logic.
5. Google Forms – Basic web-based form creation tool.
6. Magpi Forms – Mobile-friendly form designer for surveys and data collection.

 

2. Data Collection on Mobile Devices

Engineers, transport service personnel, and researchers use mobile devices to collect data in the field.

Many tools support barcode scanning, GPS tracking, image capture, voice-to-text input, digital signatures, and many other functionalities.

Mobile data collection tools can also capture data offline, store it locally, and synchronize it with a server once an internet connection is available.

Some of the tools used to collect data using mobile devices include:

 

1. ODK Collect – Open-source mobile app for mobile data collection using ODK. ODK Collect can collect data offline.
2. KoboCollect – Mobile app for data collection using KoboToolbox.
3. SurveyCTO Collect – Secure, offline-first data collection platform.
4. Survey123 by Esri – GIS-enabled app for geospatial data collection.
5. CommCare – Mobile case management tool used in health and humanitarian projects.
6. TaroWorks – Salesforce-integrated data collection tool.
7. Magpi+ – Supports multimedia data input.
8. Dimagi CommCare – Supports longitudinal tracking and case management.

 

 

Survey tools enable the creation of digital forms that capture diverse data: text, GPS, barcodes, images, and voice. Picture/Courtesy

 

 

3. Offline Data Collection: Capturing Data Without Internet Access

The ability to work offline and automatically sync data upon reconnection is a key advantage offered by modern data collection tools

Some of the mobile tools for offline data collection include:

 

1. ODK Collect – Stores responses offline and syncs later to a cloud server.
2. KoboCollect – Stores responses offline and syncs later to a cloud server.
3. Magpi+ – Designed for low-bandwidth regions.
4. TaroWorks – Works offline and syncs with Salesforce CRM.
5. CommCare – Enables offline case tracking for healthcare and NGOs.
6. Surveys on Tab – Offline-first solution for market and corporate surveys.

 

 

Offline mobile data collection allows for data capture without the internet, which can then be synchronized with cloud storage when connectivity is restored. Picture/Courtesy

 

 

4. Data Synchronization: Uploading & Syncing Data to the Cloud

With restored internet connectivity, mobile data collection tools ensure that recorded data is automatically synchronized to centralized servers, either cloud-based or on-premise, for processing.

Some of the mobile tools for data synchronization include:

 

1. ODK Central – Store and manage synchronized data.
2. ODK Aggregate – Store and manage synchronized data.
3. KoboToolbox Servers – Store and manage synchronized data.
4. Google Sheets API – Auto-syncs data to spreadsheets for easy access.
5. RedCap – Secure data management for research and healthcare projects.
6. ODK Cloud, Microsoft Azure, AWS S3, Digital Ocean, Google Cloud – Secure cloud-based data storage solutions.

 

 

5. Data Management: Cleaning, Processing, and Storing Data

Collected data needs to be cleaned, processed, and organized to facilitate analysis and informed decision-making.

Some of the tools for data management include:

 

1. Microsoft Excel & Google Sheets – Used for basic data cleaning and filtering.
2. Power BI – Dashboard creation and business intelligence reporting.
3. Python & R – Advanced data processing and analytics.
4. Tableau – Data visualization and storytelling.
5. QGIS – GIS software for geospatial data mapping.
6. Google BigQuery – Cloud-based big data warehousing.

 

 

Data processing in transport planning is crucial for analyzing travel patterns, predicting future demands, and optimizing infrastructure development. Picture/Courtesy

 

 

6. Reporting & Action: Analyzing Data for Decision-Making

Organizations use processed data to create reports, visualize insights, and inform decision-making.

Some of the tools for reporting & action include:

 

1. Microsoft Power BI – Interactive data visualization and reporting.
2. Google Data Studio – Cloud-based business intelligence platform.
3. Tableau – Advanced analytics and visualization.
4. SPSS & Stata – Statistical tools for complex data analysis.
5. QGIS – GIS mapping and spatial analytics.
6. Looker (Google Cloud) – Data-driven business intelligence platform.

Case Studies of Mobile Data Collection in Transport & Infrastructure

The following is a list of projects and case studies where transport and infrastructure projects have successfully adopted mobile tools and other modern modes of data collection:

 

1. KoboToolbox in Remote Appraisal Supervision, Monitoring, and Evaluation (RASME) of Infrastructural Development Projects in Mozambique

 

Remote Appraisal, Supervision, Monitoring, and Evaluation (RASME) is an initiative that leverages information and communications technology (ICT) to enhance the management of development projects.

The African Development Bank (AfDB) is a key driver of the RASME initiative, collaborating with partners like the World Bank.

 

Project Details

 

1. In April 2022, Mozambique joined the African Development Bank’s (AfDB) Remote Appraisal Supervision, Monitoring, and Evaluation (RASME) project.
2. The Southern African country became the sixth nation to adopt this digital data supervision system.
3. RASME relies on the KoboToolbox platform, an open-source data collection tool to enhance the monitoring and evaluation of development projects in remote regions.
4. This is a part of Mozambique’s broader strategy to enhance data management in development projects, aligning with the AfDB’s objectives to support innovative data collection solutions across the continent.

 

 

Challenges Before the Adoption of Mobile Data Collection in Monitoring Mozambique’s Infrastructure Projects

 

 

1. Data was collected manually, leading to delays and increased potential for errors.
2. Decision-makers had restricted access to real-time data, hindering timely interventions.
3. Monitoring projects in remote areas was logistically challenging, affecting data accuracy and completeness.

 

 

 

A landmark bridge along one of the highways in Mozambique’s Manica Province. Picture/Courtesy

 

 

Key Benefits After the Adoption of Mobile Data Collection

 

1. Automated validation rules by KoBoToolbox ensured accurate and consistent data collection.
2. The digital system reduced the time and resources required for data management.
3. Access to up-to-date information allowed for more informed and timely project decisions.
4. Local communities benefitted from more effective monitoring and improved infrastructure.
5. Development partners benefitted through improved data availability facilitating better coordination and support.
6. There was enhanced capacity for project oversight and management.

 

Source

Mozambique joins collaborative ICT data collection initiative developed by AfDB – Africa Business in Brief

 

 

2. ODK in Assessing the Impact of Road Infrastructure Development Projects on Local Communities in Peri-Urban Areas of Kisumu, Kenya

The growth of road infrastructure has significantly accelerated urbanization in Africa and other Global South regions.

Improved connectivity makes peri-urban areas more attractive for residential and commercial development, leading to increased real estate value and economic growth.

Both Kisumu City, Kenya, and Accra, Ghana, along with their respective peri-urban regions, have seen positive effects from expanded road networks.

Kisumu has benefitted from the Northern Corridor Transport Improvement Project (NCTIP), an international road to transit goods being implemented in Kenya.

Accra also cashed in on a toll road highway expanded in 2008 by the Government of Ghana with donor financial support to ease traffic from Greater Accra to Central regions.

 

Project Details

 

1. Scholars from the University of Twente in the Netherlands conducted a study in 2020 to assess the impact of road infrastructure projects on local communities.
2. During their research in Kisumu, the researchers adopted the Open Data Kit (ODK) to collect primary data from residents.
3. KoBoToolbox was adopted for the parallel study conducted in Accra, Ghana. The tools were adopted for their ease of use and familiarisation by the data collectors.
4. Both studies recorded enormous economic growth that was driven by infrastructure projects in the respective areas.

 

Challenges Before the Adoption of Mobile Data Collect in Infrastructure Impact Studies

 

1. Data was collected manually through paper surveys, which were prone to human error and inefficiencies.
2. Collected data had to be manually transcribed, leading to delays in analysis and reporting.
3. Given the manual process, data quality was often compromised, with incomplete or inconsistent responses.
4. In remote or hard-to-reach areas, reaching respondents with paper-based methods was both time-consuming and costly.

 

 

The legendary Kit Mikayi rock formation near Kisumu City. Kisumu has benefitted from the Northern Corridor Transport Improvement Project (NCTIP) connecting it to the larger East African region. Picture/Courtesy

 

 

Key Benefits After the Adoption of Mobile Data Collection

 

1. ODK’s built-in validation rules helped reduce errors in data collection and ensured consistency across all surveys.
2. With mobile devices and real-time data syncing, data collection was quicker and more efficient, allowing the project team to make timely decisions.
3. Mobile devices drastically reduced the costs of data collection.
4. The use of mobile-based tools allowed for easier reporting, and stakeholders could access updated data at any time, improving decision-making.

 

The primary beneficiaries of this project were the local communities in the peri-urban areas of Kisumu, who through the study were able to have improved access to social services like education, healthcare, and markets.

 

Source

The Impact of Road Infrastructure Development Projects on Local Communities in Peri-Urban Areas: the Case of Kisumu, Kenya and Accra, Ghana – Faculty of Geo-Information Science and Earth Observation of the University of Twente.

 

 

3. Drones in Monitoring Traffic Congestion in New South Wales (NSW), Australia

Traffic congestion continues to pose serious problems across continents, from Africa’s vibrant urban centers to America’s vast highway networks and Australia’s busy streets.

Daily, traffic congestion leads to wasted time, increased fuel consumption, heightened pollution, and diminished economic productivity.

In New South Wales, Australia, particularly in Sydney, traffic congestion is a persistent problem. Authorities have turned to real-time data from drones to manage the menace caused by the city’s dense population.

 

Project Details

 

1. In 2024, Transport for NSW deployed a fleet of more than 70 drones across key traffic areas in New South Wales.
2. The Australian media reported this feat as an innovative approach to monitor traffic congestion and improve road safety in the metropolis.
3. The drones assist in providing real-time data to traffic apps, monitoring traffic during peak hours, and managing road incidents.
4. Leichhardt, Sydney was designated as the Drones Operating Hub.

 

 

Challenges Before the Adoption of Drones in Sydney’s Traffic Congestion Management

 

1. Traffic accidents and road disruptions were difficult to monitor and respond to quickly, leading to extended congestion.
2. Traffic monitoring was largely dependent on static cameras and traditional sensors, which lacked the flexibility and immediacy required for fast-moving incidents.
3. Major events like public festivals and races caused blockages, and traffic management was often reactive rather than proactive.

 

 

Drone image of city traffic congestion. Picture/Courtesy

 

 

Key Benefits After the Adoption of Drone Technology

 

1. Drones allow for quicker assessment of traffic incidents, enabling faster detours and reducing congestion caused by accidents.
2. Drones offer a bird’s-eye view of traffic, providing up-to-date information that was previously unavailable with traditional monitoring systems.
3. Drones were deployed for major events like the Sydney World Pride, improving crowd and traffic management.
4. The real-time streaming from drones allows for rapid decision-making, which helps mitigate potential traffic problems before they escalate.
5. NSW residents benefit from reduced congestion and faster incident management, leading to a smoother travel experience.
6. The drones provide emergency services with quicker, more accurate information to manage road incidents and deploy resources effectively.

 

Source

A fleet of drones is being deployed to monitor NSW traffic – Cyberdaily.au

 

 

4. Monitoring and Analyzing Traffic Using Sensors in Kent, England

Kent is a ceremonial county located in the southeastern part of England, and it’s a region rich in history, natural beauty, and cultural significance.

It is often referred to as “the Garden of England” due to its lush countryside, fruit orchards, and hop gardens.

 

Kent experiences significant traffic congestion, particularly on its major roads like the M20 and M2, with authorities increasingly utilizing drones to monitor traffic flow and incidents.

 

Project Details

 

1. Kent County Council, in collaboration with transportation experts, implemented sensor-based technology to monitor and analyze traffic flow across key areas in Kent.
2. The project began in 2018, with the implementation of sensors across various key roads.
3. It involved a combination of road surface sensors, infrared sensors, and cameras for data collection.
4. The technology could distinguish between cars, bicycles, buses, and pedestrians while recording their speeds and counting the number being used.

 

 

Challenges Before the Adoption of Specialized Sensors in Traffic Data Collection

 

1. High traffic volumes during rush hours and events led to persistent congestion, especially on major highways like the M25 and roads connecting to London.
2. Traditional traffic monitoring methods were limited, often relying on outdated or static data that did not provide real-time insights into traffic flow and congestion patterns.
3. Traffic signals and roadworks were often managed based on estimates, rather than dynamic, real-time data.
4. Commuters frequently expressed frustration with traffic jams and delays, which were not always addressed effectively by existing infrastructure.

 

 

Traffic navigating through the compact narrow streets of Kent, England. Picture/Courtesy

 

 

Key Benefits After the Adoption of Sensors in Traffic Management

 

1. Sensors enabled the optimization of traffic signal timings, reducing wait times and improving the flow of vehicles.
2. Traffic incidents, such as accidents or breakdowns, were detected more quickly through sensors, enabling rapid response from authorities and reducing disruptions.
3. Commuters could receive up-to-date information through apps or websites, allowing them to plan their routes and avoid congested areas.
4. The sensor data provided valuable insights into traffic patterns, enabling Kent County Council to make informed decisions for long-term infrastructure development.

 

Source

How traffic sensors and cameras are transforming city streets – CNBC

 

 

Also read: Mobile Data Collection: Unlocking Efficiency in the Energy Sector

 

 

5. Mobile GPS Data Collection for Nairobi’s Semi-formal Bus System

Nairobi’s public transit has evolved from early bus services to a dominant “matatu” culture, characterized by privately owned minibusses that provide popular but often chaotic transport services.

Efforts to streamline the largely semi-formal transport system have been underway for the past decade, involving massive data collection campaigns.

These semi-formal bus networks, driven by profit, consist of numerous private operators, with ownership ranging from individual drivers to businesses and SACCOS, much like taxi services.

 

Project Details

 

1. In 2014, a group of researchers drawn from Kenya’s University of Nairobi, America’s Massachusetts Institute of Technology (MIT), and Columbia University ventured to Nairobi.
2. The team successfully collected data on 135 routes that comprise Nairobi’s matatu system.
3. The University of Nairobi led the data collection process with a team of five students who performed most of the fieldwork.
4. Armed with GPS-enabled mobile Apps like MyTracks, the students documented route and stop names as well as physical characteristics of the stops.
5. This was the first time these routes were mapped comprehensively and validated using the Google GTFS validator.
6. Google GTFS (General Transit Feed Specification) is a standardized format for public transportation schedules and related geographic information.
7. It allows transit agencies to provide their data to Google and other developers, making it easier for people to plan trips using public transportation.

 

 

Challenges Before the Adoption of GPS Technology in Mapping Transit Routes

 

1. There was minimal data on the actual routes taken by buses, leading to inefficiencies in route planning and delays.
2. The schedules were not standardized, and passengers often faced uncertainty regarding bus arrival times.
3. Traffic congestion and unsafe driving practices were prevalent due to limited monitoring and management tools for the buses.
4. Different bus operators managed their routes independently, with no centralized system for coordinating schedules or improving service efficiency.

 

 

An overhead shot of traffic around Nairobi’s Globe Roundabout on a Saturday morning. Picture/Courtesy

 

 

Key Benefits After Mobile GPS Adoption

 

1. By tracking the actual routes taken by buses, planners could optimize bus routes, reduce delays, and improve travel times.
2. GPS tracking allowed for better monitoring of buses, encouraging safer driving practices and more efficient use of road space.
3. Nairobi’s residents, particularly daily commuters, were the primary beneficiaries of this project, as they experienced shorter wait times, more reliable services, and safer travel.
4. The City County Government gained valuable data that helped in urban planning, traffic management, and infrastructure development to support public transport.

 

 

Source

The digital matatu project: Using cell phones to create open source data for Nairobi’s semi-formal bus system – Journal of Transport Geography

 

Conclusion

The integration of mobile data tools and other advanced data collection technologies has significantly transformed the transportation and infrastructure sectors.

 

Mobile GPS, sensors, drones, and other data tools have provided real-time insights into transportation systems, enabling better decision-making for city planners, governments, and businesses.

 

In public transport, for example, these tools have improved route planning, optimized traffic flow, and enhanced service reliability, leading to greater commuter satisfaction.

 

Ultimately, the adoption of these technologies helps develop a more connected, responsive, and adaptive transportation network.

Post Tags:#Drones#GIS#GPS#KoBoToolBox#ODK#Sensors