<p>At the heart of modern traffic and transport logistics are advanced data analytics and data engineering, key technologies that are revolutionizing transport and delivery services. They not only enable more efficient route planning and cost reduction, but also a significant improvement in delivery reliability. Through the intelligent use of real-time data and predictive analyses, companies can minimize downtimes and increase the efficiency of their means of transport. </p> <p>Our offering includes customized solutions that are specifically tailored to the challenges and needs of the logistics industry. From the development of machine learning models for predictive maintenance to the optimization of transport routes using real-time traffic data, we offer comprehensive services. These enable our customers to effectively reduce transportation costs, increase the reliability of their deliveries and ultimately ensure more sustainable operations. </p> <p><a href="https://www.2moove.de/use-cases/verkehrsnachfrage-und-prognose/">Practical example</a></p>

<h2>Reduction of transportation costs:</h2> <h6>Detailed analyses of transport routes, fuel consumption and other relevant factors can be used to identify potential savings. This helps companies to effectively minimize their transport costs. </h6> <ul> <li><strong>Increasing fuel efficiency and reducing costs</strong>: Detailed fuel consumption analyses identify potential savings, reduce operating costs and support environmental protection.</li> <li><strong>Optimization of delivery times and vehicle utilization</strong>: the use of algorithms for route planning and reducing empty runs improves efficiency and reduces transport costs.</li> <li><strong>Adaptability to market dynamics through dynamic contract management</strong>: Flexible pricing and contract adjustments enable cost reductions by taking advantage of favorable market conditions.</li> </ul> <p> </p> <p><strong style="margin-bottom: 20px">Concrete measures and services</strong>:</p> <ul> <li><strong>Fuel consumption analysis and optimization</strong>: Perform detailed analyses of fuel consumption under different conditions and routes to identify potential savings. Customers benefit from tailored fuel efficiency recommendations that contribute directly to reducing transportation costs. </li> <li><strong>Development of optimization models for route planning</strong>: Use of algorithms and machine learning to determine the most optimal routes based on historical data and real-time traffic information. These models enable companies to optimize transport routes, resulting in shorter travel times, reduced fuel consumption and therefore lower transport costs. </li> <li><strong>Analysis and reduction of empty and detour journeys:</strong> use of data analytics to identify inefficient routes and unused capacity. Customers can save significantly on transport costs by optimizing their transport routes and making more effective use of their vehicles. </li> <li><strong>Dynamic pricing and contract management</strong>: Using data engineering to develop dynamic pricing models and efficient contract management for freight costs. By analyzing market trends and freight rates, companies can negotiate more favorable contract terms and further reduce their transportation costs. </li> </ul>

<h2>Prediction-based maintenance of means of transportation:</h2> <h6>Use of machine learning models to analyze operating data for preventive maintenance, reducing downtimes and increasing the efficiency of means of transport.</h6> <ul> <li><strong>Proactive maintenance</strong>: The use of machine learning for maintenance prediction enables proactive maintenance, avoids breakdowns and optimizes the service life of means of transport.</li> <li><strong>Increasing efficiency and reducing costs</strong>: analyzing vehicle telematics provides insights into vehicle performance, supports precise maintenance interventions and reduces operating costs in the long term.</li> <li><strong>Optimization of maintenance management</strong>: Dashboards for maintenance management and data-based maintenance plans improve the planning and execution of maintenance work, reduce downtimes and extend the service life of vehicles.</li> </ul> <p> </p> <p><strong style="margin-bottom: 20px">Concrete measures and services</strong>:</p> <ul> <li><strong>Development of machine learning models for maintenance prediction</strong>: use of algorithms to predict maintenance requirements from historical operating data. This service enables proactive maintenance planning, reduces unexpected downtimes and optimizes the service life of means of transport. </li> <li><strong>Analysis of vehicle telematics for condition monitoring</strong>: Collection and evaluation of telematics data to monitor the condition of vehicle components in real time. Customers benefit from a deeper understanding of vehicle performance, which enables precise maintenance interventions and reduces operating costs in the long term. </li> <li><strong>Provision of dashboards for maintenance management</strong>: Development of user-friendly dashboards that display maintenance requirements, history and forecasts. This supports companies in the efficient planning and execution of maintenance work by providing transparency on the maintenance status and helping to optimize the use of resources. </li> <li><strong>Creation of customized maintenance plans based on predictive analytics</strong>: Use of data analysis to create individual maintenance plans for each means of transport. Customers receive customized maintenance strategies based on specific operating patterns, which leads to an extension of the service life of the means of transport and a reduction in downtimes. </li> </ul> <p> </p>