Project Senslog

The use of sensors in logistics is becoming more common. Nowadays, the industry is more likely to adopt sensory technologies. Consequently, more sensory data is available. However, academic literature and practical experience show outdated methods are used to analyze this data. Furthermore, current optimization models are not designed to exploit sensory data insights. Without these methods, the sensory data is practically “useless”.

State-of-the-art sensors, such as the ones developed by project partner Itude Mobile, capture multi-dimensional data in containers (e.g. temperature, light, pressure and movement differences). This information is traditionally used to monitor product quality in containerized freight transport. However, the industry lacks appropriate algorithms to accurately identify what changes in multi-dimensional measurements are exceptional and require intervention or rescheduling.

The SensLog project team tackles the above-mentioned challenges. We develop models and methods to use the newly captured information on container equipment and cargo. In addition, we are looking for real-life cases (pilots) within different industries. These will be used to discover opportunities to improve the implementation of innovative sensors in logistic operations. Furthermore: these will encourage logistic companies to explore and implement data driven strategies in order to improve their market position. Within these pilots we hope to increase the efficiency of multi-modal containerized transport. Resulting in a stronger position of the Netherlands as a leader in creating, developing and demonstrating innovative concepts in logistics. 

Our research objectives
  1. Supporting the adoption of logistics sensory data by optimizing the number of sensors required to obtain the targeted quality of the sensory data and by efficiently repositioning sensors in the supply chain.
  2. Efficiently deriving appropriate and correct insights from logistics sensory data to generate predictive models for logistics operations (i.e. detect exceptions to guide logistics planning, and predict equipment requirements in supply chains) to improve logistics performance.

Achieving these research objectives is essential to effectively implement sensory data in the (logistics) decision making process. The project stresses the importance of implementing the scientific results in daily practice and therefore the partnership with the industry is considered crucial.

The project outcomes (models, data analysis and optimization methods and insights) will be translated into market oriented services and working solutions for participating companies.

The following people at VU Amsterdam are part of the SensLog project team:

Wout Dullaert, Professor Logistics and Supply Chain
Joaquim Gromicho, Professor of Applied Optimization in Operations Research
Said Dabia, Associate Professor of Transport Optimization
Denise Tönissen, Assistant Professor in Logistics
Claudio Ciancio
Research Associate in Logistics

The Logistics and Operations Research groups of VU Amsterdam have joined forces with two leading industry partners in the field:

Itude Mobile
Itude Mobile develops innovative solutions for supply chains, such as innovative sensors (Babbler) that enable the monitoring of supply chains at an unprecedented scale. The large- scale data generated by Babbler will be used to test the developed methods and to validate the business cases. Itude Mobile provides data, feedback and guidance throughout the project and participates in validating the project outcomes in real-life business cases.

The following people from Itude Mobile are closely involved in the project:
Robin Puthli (Founder and CEO of Itude Mobile and Babbler)
Simon Vos (IT and Data Science specialist) 

Itude logo 

ORTEC has a wide experience and track record in logistics optimization. ORTEC’s logistics solutions range from strategic network optimization to tactical and operational route planning and vehicle planning. In the last few years, ORTEC has increasingly built up experience in data
analytics ranging from descriptive to predictive and prescriptive analyses. In the SensLog project ORTEC will lend their expertise in optimization and data mining techniques.

The following people from ORTEC are closely involved in the project:
Ronald Buitenhek (Data Scientist)
Noud Gademann (Supply Chain Lead Consultant) 

  Ortec logo

The project team is always looking for new opportunities to use their scientific expertise in logistic sensory data. If problems exist within your field of expertise and you would like to explore these more, please contact us via