Bus fleet management software: 95% accuracy in real-time bus fleet tracking

Azure

Business intelligence

Data analytics

Data management (DMS)

IoT

Web

Innowise developed an interactive dashboard for a bus fleet management software, improving the monitoring of bus fleet operations and enhancing the accuracy of bus schedules, passenger counts, and service reliability.

Customer

Industry

Logistics

Region

Client since

2022

Our client is a prominent bus operator, recognized for its significant role in the public transport sector, especially in Sweden. The company is known for its wide range of transportation services, including procured public transport, school traffic, commercial line, and on-demand services.

Detailed information about the client cannot be disclosed under the provisions of the NDA.

Challenge

Enhancing the overall functionality and usability of the bus fleet management software

The client’s previous transport fleet management software, primarily focused on bus fleet management, began to reveal significant limitations. The challenges were multi-dimensional, stemming from a dashboard that failed to accurately track and report key operational metrics and the allocation of resources. These shortcomings became increasingly evident in several areas:

Inaccurate bus movement and resource allocation tracking: The client’s bus fleet management software struggled with correctly monitoring bus routes, leading to discrepancies in arrival and departure times. This issue was compounded by the inability to identify the reasons behind trip cancellations or delays, as well as properly tracking driver workload.
Faulty passenger count: A critical flaw was the system’s ineffectiveness in tracking the number of passengers boarding and alighting. This resulted in unreliable data, impacting the client’s ability to make decisions regarding route planning.
Data interpretation errors: The existing dashboard, designed to interpret vast amounts of data, was riddled with miscalculations, leading to a distorted view of the operational efficiency and service quality.
Statistical inconsistencies: There were noticeable inconsistencies in the statistical reporting, which hindered the ability to perform trend analysis for resource allocation.
User experience challenges: The user interface of the pre-existing dashboard was not intuitive, making it difficult for staff to navigate and extract information.

Given these multifaceted challenges, the client sought our expertise to overhaul their dashboard system. The goal was to develop a solution that not only rectified these specific issues but also enhanced the overall functionality and usability of the bus fleet management software.

Solution

Bus fleet GPS tracking software with real-time data tracking, interactive dashboards, and predictive analytics

We developed an enhanced dashboard system for the bus fleet GPS tracking software, focusing on accurate real-time data tracking and user-friendly functionality. Based on integrated IoT and data analytics technologies, the solution effectively addressed the client’s need for precise monitoring of bus movements, passenger counts, and schedule adherence

Development of an interactive dashboard

Our team developed an interactive dashboard utilizing the data obtained from IoT sensors, which were integrated into an Azure SQL database. This combination was selected for its real-time data processing capabilities and ability to handle large datasets without sacrificing performance. The dashboard provided live updates on bus locations, arrival times, and passenger counts. Key features included:

Geological tracking: Real-time tracking of each bus, offering a detailed fleet overview.
Time-sensitive alerts: Automated alerts for delays or deviations from the schedule, enhancing operational responsiveness.

Enhancement of data accuracy

In our quest to maximize data accuracy, we employed advanced algorithms and analytics into the bus fleet GPS tracking software. We leveraged Python and its libraries, Pandas and NumPy, to handle and process complex datasets. Here is an in-depth look at the specific functionalities and their impact on logistics operations:

Predictive analytics

Route optimization: Our models analyze historical and real-time traffic data to suggest the most efficient routes, helping to reduce delays and fuel costs.
Delay forecasting: By examining patterns in traffic flow, weather conditions, and historical delays, the system predicts potential disruption for proactive scheduling.
Passenger flow analysis:Predictive tools assess passenger volume trends, aiding in optimizing bus schedules and frequencies.

Data reconstruction and advanced tracking

Filling data gaps: The bus fleet management software identifies and fills missing or inconsistent data points.
Vehicle health monitoring: Real-time tracking of vehicle health indicators like fuel levels and maintenance needs for preemptive upkeep and reducing downtime.
Operational KPI tracking: Key Performance Indicators (KPIs) such as on-time performance and trip completion rates are continuously monitored for improvements.

User roles and interactivity

Our enhanced dashboard system for the bus fleet management software was designed with specific user roles to cater to varying levels of interaction and operational needs:

Viewer role

Real-time data visualization: Viewers have access to a dynamic map displaying real-time bus locations, route progress, and estimated arrival times.
Customizable analytics dashboard: By examining patterns in traffic flow, weather conditions, and historical delays, the system predicts potential disruption for proactive scheduling.
Predictive analytics: Viewers can access predictive models forecasting potential delays, enabling preemptive route adjustments and scheduling.
Sharing insights: The dashboard allows for easy sharing of findings and reports with colleagues, enhancing collaborative decision-making.

Administrator role

Comprehensive system control: Administrators have overarching control over the dashboard’s settings, ensuring the system aligns with organizational requirements.
User access management: This feature allows for the management of user permissions, ensuring staff access is tiered and secure.
Data management and reporting: Administrators can oversee the data collection, analysis, and reporting.
System customization: They can customize the dashboard’s interface and functionalities to adapt to changing conditions or to integrate new data sources.

Technologies & tools

Back-end

Python, Flask, Pandas

Databases

Azure SQL

Platforms

Microsoft Azure, Power BI

Operating systems

Windows Server, Linux

Web Server

Apache, Nginx

Integrations

Azure IoT Hub

Server monitoring

Prometheus, Grafana

Process

Our project to develop the bus dashboard system for a bus fleet management software unfolded through a series of meticulously planned stages, ensuring each aspect of the solution was aligned with the client’s needs:

Initial stage – understanding requirements: Our team commenced with a deep dive into the client’s existing transport fleet management software. We focused on identifying the key challenges and areas for enhancement, laying the groundwork for a tailored solution.
System design: The next step involved designing the system’s architecture. Here, our emphasis was on data handling and smooth integration with IoT sensors.
Agile development: With a clear design in place, we proceeded with a software development stage, leveraging Agile principles. By utilizing Python and related libraries, our team focused on enhancing the back end to processes. We analyzed large datasets, integrating them with Azure SQL and IoT Hub.
Testing: The updated bus fleet management software was rigorously tested after development. We targeted the back end’s data accuracy and the system’s reliability, particularly in its integration with IoT devices.
Deployment and training: After successful testing, the system was deployed. We guided the client’s team, focusing on how to manage the system and interpret the data.
Ongoing support: Post-deployment, our team remained dedicated to supporting the client, particularly in ensuring data accuracy and system functionality.

Team

Project Manager

Full-Stack Developer

Data Analyst

BI Developer

QA Engineer

Results

95% accuracy in bus fleet tracking and 2x faster data analysis

The implementation of our dashboard system for the bus fleet management software primarily enhanced data accuracy, which led to a near-perfect accuracy of bus arrival and departure times. This improvement was crucial for streamlining the scheduling process and reducing wait times for passengers. Operational delays were reduced by approximately 30% due to more efficient route management enabled by predictive analytics. The dashboard’s data analysis tools allowed the client’s team to identify operational bottlenecks more quickly, leading to an increase in the speed of decision-making processes related to fleet management. This was particularly evident in the areas of resource allocation. The newly designed user-friendly interface of the bus fleet management software reduced the average time required for staff training, making it easier for new and existing employees to adapt to the system. This improvement also contributed to a smoother workflow within the team.

Overall, these enhancements in the bus fleet management system contributed to a more efficient, timely, and reliable service, aligning with the client’s objective of improving operational performance and customer satisfaction.

Project duration

October 2023 - December 2023

faster data analysis

95%

accuracy in arrival and departure time tracking

Related cases

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Bus fleet management software: 95% accuracy in real-time bus fleet tracking

Customer

Challenge

Enhancing the overall functionality and usability of the bus fleet management software

Solution