Our Projects

Data OPS Engineering

for National Database Road Traffic Data

Context & Objectives
In August 2020, the Netherlands was the first country in the world to create a digital overview of all national road signs. The data from the signs in addition to real-time traffic data at the Dutch roads are stored digitally and are available as open data via APIs or portals such as the Nationale Databank Wegverkeersgegevens (NDW) portal and the Dexter application. In practice, any user can have access to real-time and historic data regarding the number of vehicles, the average speed, the signboards, the bridges, the incidents, at any moment and at any place in the Dutch road infrastructure. In addition, there are available data-sets regarding average traveling time and bicycle intensity. All this information comes from multiple data-sources and partners such as TomTom GPS device, T-Mobile, Flitsmeister, etc. and they are placed in a centralized data storage. This development is commissioned by Rijkswaterstaat and my role in this project is the Data Ops Engineer within the Big Data team at NDW.

Results & Added value
My daily routine consists of Data engineering tasks regarding data cleaning and ETL issues. Moreover, I participate in software development sprints as Python developer. In addition to my Data Ops Engineering role, I am a first-point of contact engineer in our Helpdesk team. All these actions, help my team to maintain and evolve our traffic information system and infrastructure, which serves hundreds of individual users and scientists, to work with traffic data. The quality of our work allows authorities, road users, and analysts to receive up-to-date information about the traffic situation in the Netherlands because accurate and reliable data can contribute to increasing road safety.

Keywords:

  • Software Development: Python, Kubernetes
  • Data Management: Postgres
  • Cloud: Azure Data Blob & Datalake Storage
  • Project Management: Scrum, Azure DevOps

 

Data Streaming

for Sunfounder Picar-S Digital Twin

Context & Objectives
Digital twins are virtual replicas of physical devices and they can be used to run simulations before actual devices are deployed or to prevent potential failures. At CIMSOLUTIONS there is a Digital Twin Competence Center, which works on the concept idea of the creation of a Digital Twin Dashboard. The intention of this Dashboard is to become the digital copy of a Raspberry Pi Auto-vehicle. More specifically, a Raspberry Pi mini-car with connected sensors regarding its dynamics (such as speed, acceleration, wheels rotation, etc) and its environment (such as temperature, humidity, etc) communicates with a base station. The base station implements a Dashboard where the user can see the environmental parameters and the dynamics of the vehicle. As a result, this work focused to implement the most accurate version of this mini-car representation in the Dashboard.

Results & Added value
My role in this project was to assemble the SunFounder PiCar-S, attach the Raspberry Pi on top of the car, and connect all the sensors to the Pi interface. In addition, I installed all the libraries to enable our software to read the data from the sensors, and with the use of Python, I have achieved to establish a data stream between the car and the base station. This data stream is the actual data representation of the current state of the car in terms of speed, wheels rotation, wheels angle, and direction. These values are used from the Dashboard and implemented as a whole the digital twin of the mini-car. This specific Dashboard is a virtual representation of the mini-car and can predict potentials threats in real-time time. For example, if the car makes a turn and the rotation speed of the left front wheel is different from the rotation speed of the right front wheel, then there is a potential danger such as under-steer or over-steer.

Keywords:

  • PiCar: SunFounder PiCar-S Kit V2.0 for Raspberry Pi
  • Software Development: Python, C# WPF
  • Project Management: Scrum

 

Data Analytics

for Managed Technology Services

Context & Objectives
The main focus of Philips Healthcare is to be transformed from a supplier to a partner of any healthcare provider. Not just in the medical world, but in all kinds of markets, companies want to work more efficiently, and they are asking their suppliers to help them do so. They want to know exactly what they can expect from the products and the systems they purchase, not just in the short term but also in ten or even twenty years’ time. In this new role, Philips takes responsibility for everything. They plan, maintain, manage and sometimes they even finance the technology as well. Philips ensures that clinical departments use the right equipment and that the hospital derives the maximum return on its investments. At Philips, the Managed Technology Services (MTS) team is taking the lead in this fantastic new role.
As a Data Analyst, within the MTS team, my assignment focused on Data Analytics regarding the Maintenance Services of Philips. More specifically, I supported customer projects by helping Philips advisers in the healthcare field to present technical aspects of the hospital equipment to our healthcare partners and by creating customer-facing reports. My main task was to access and handle different data sources and available reporting tools, regarding healthcare equipment. With the use of these specific sources, I generated, standardised, automated and tested the scheduled and ad-hoc report creation.

Results & Added value
The outcome of my work enables Philips Business Analyst and Advisers to automate their reporting tasks and to reduce their effort of making customer analytics. Moreover, my work supported Philips to standardise the reporting process all over the world by creating a standard report template, which is independent of the local markets.

Keywords:

  • Data Analysis: QlikSense, Microsoft Excel
  • Software Development: Python - Visual Studio IDE - PowerShell Scripting
  • Data Management: SAP - Teradata - Salesforce - OneEMS

 

Project Management

for an Autonomous Flying Drone

Context & Objectives
The Netherlands has, along with Austria, the best waste management program in Europe, according to a recent report from the European Commission [https://europa.eu/rapid/press-release_IP-12-888_en.htm?locale=en]. However, after a walk in Eindhoven's city center, you are more likely to get depressed and angry at the sight of other people’s rubbish, from casual litter to deliberate fly-tipping. While littering of the oceans is now at the forefront of public concern, general littering of the countryside and communities is barely on the national radar. Yet the amount of “eyesore” litter, not just plastic, is increasing exponentially on roadsides, in rivers, in public spaces, and in the countryside and has a hugely negative impact on people’s lives. The proactivity and personalization of the services should be the action guide of the public function in the very near future, and as a result municipalities are vital to this new era.
This project focused on the concept idea of the creation of an autonomous flying drone, which could help the authorities to keep the cities clean. A drone that could fly alone in the city, recognise all the garbage in the streets and then sends a heatmap to the authorities about where they should clean today.

Results & Added value
The outcome of this work is in the form of a Matlab script, which receives the coordinates of a specific location and commands a drone to scan this specific area for garbage. More specifically, the drone will fly in a pattern which has been imported from Matlab, covering the whole area and it will take real-time images for classification. Once the whole area is scanned drone will return to the base and a report will be generated with all the information about its flight, the covered area and the garbage, which has been found. 

Keywords:

  • Drone: AR. Drone 2.0
  • Software Development: Matlab and Neural Networks libraries
  • Project Management: Agile

 

Datawarehousing

for Human Resources

Context & Objectives
Viggo Eindhoven Airport B.V. is the largest service provider in Eindhoven Airport, with 42-years history, and offers total solutions in ground handling, cargo, security and cleaning services. For this purpose, Viggo employs more than 6 hundred operators, who cleverly integrate the existing links in the service chain, on a daily basis. As every company that wants to excel, Viggo collects and analyzes big data, regarding its employees, in order to improve its services and to keep the leadership among its competitors. This project focuses on the design, the implementation and the analysis of a data warehouse, specialized in human resource analysis, within Viggo.

Results & Added value
More specifically, a data warehouse system is created, focused on HR department business analysis, which converts the input spreadsheets into a fully centralized data warehouse, with the use of icCube [https://www.iccube.com/human-resources-analytics-eindhoven-airport/]. From an academic purpose, two problems are discussed, within this project. The former is the data warehouse design form based on human resources analysis and the latter is regarding Extract, Transformation and Loading (ETL) solutions for spreadsheet-based sources.

Keywords:

  • Software Development: C# .NET - Visual Studio IDE - JAVA - Netbeans IDE
  • Version Control: TortoiseSVN
  • Data Management: MySQL - MySQL Workbench
  • Data Warehousing: CSVQL - icCube Server
  • Other: Prince2

 

Data Engineering & Automation

for SITA Messaging

Context & Objectives
The aviation industry has a considerable need for exchanging effective, global communications on a daily basis. SITATEX IP is the leading operational mail service in the air transport industry (ATI). It generates and receives ATI-specific Type B messages through an intuitive mail interface. Over 20,000 users in the ATI, across 200 countries and territories, exchange over 800 million messages every year with SITATEX IP. Eindhoven airport communicates with the rest of the airports and with the airlines via this component, which has a cost per message. As a result, there is a need for a budget for communication and back-up purposes.

Results & Added value
The output of this project is an add-on, which simplifies the back-up process and reduces the cost of messaging. More specifically, my solution concluded a cost reduction per year for Viggo Eindhoven Airport. Moreover, a 24/7 email daemon has been created, which operates real-time and extracts all the relevant to Operations info from the incoming Type B Messages at Eindhoven Airport. This extraction can be achieved only by Advanced Airport Distributed Control System and as a result, with the use of this tool, Viggo Eindhoven Airport negotiate the condition with their customers being in an advantageous position.

Keywords:

  • Software Development: C# .NET - Visual Studio IDE - SMTP Server - NLog
  • Version Control: TortoiseSVN
  • Data Management: Microsoft SQL Server - Entity Framework
  • Other: Prince2

 

Data Visualisation

for Match-Eye Project

Context & Objectives
Football managers have a demanding job because football is a game of strategy and risk management. As a result, a football manager, in order to excel, needs to be involved in football, scouting, recruiting, and previewing the performance of his own team in upcoming jobs for long hours. However, the evolution of technology has created means which can assist sports managers. A project, named 'MacthEye', focuses on the modeling and the implementation of an assistant tool, which intends to be the performance evaluation component of a football manager, by using the aforementioned GPS technology. More specifically, my task was to create a demo application, which uses a data-set, obtained from Europa League matches that took place on the home ground of the Norwegian professional team Tromso IL during November 2013.

Results & Added value
The output of my work is in form of a web application [click here] and builds an intuitive and attractive presentation of meaningful match information that directly relates to the evaluation a team performance, in terms of football skills and tactics. With the use of this web application, which is a time-series representation of the movement of Tromso IL's players, from a helicopter view perspective, a football specialist can identify the strategy of Tromso IL team, during their attacking and their defending performance.

Keywords:

  • Software Development: HTML - CSS - D3.js - JavaScript - NetBeans
    IDE
  • Version Control: TortoiseSVN
  • Data Management: MySQL
  • Other: Agile Scrum

 

NoSQL databases Research

for professional football analytics

Context & Objectives
Football community defines as the ”Twelfth Man”, the fans that cheer for their team passionately and as the ”Thirteenth Man”, the referee. Meanwhile, the ”Fourteenth Man” symbolizes all possibilities in terms of recording and analyzing data through online media, such as smart-phones, tablets, and TV. In recent times and since football is more professional than ever, the coaching staff focuses on every minor detail, which may give either a critical advantage against the opponent either the victory. Connected.Football tries to be always on the cutting edge of technology and because of this fact that there was a need for a research in the relation of Sports Analytics and Data Management. The intention of this project is to define which type of store is the most appropriate for a specific input data-set related to professional football analytics based on the paper ”Soccer Video & Player Position Data-set”.

Results & Added value
The output of the project suggests that both SQL and NoSQL have advantages and disadvantages against each other. More specifically, according to some benchmark queries NoSQL behaves better than SQL and according to some others vice versa. The result of this work has been used from Connected.Football in collaboration with the academic community in order to produce a Sports Analytics tool, which initiated several academic projects in sports analysis.

 

Keywords:

  • NoSQL Data Management: Apache Cassandra - Apache Spark - Apache Storm - Azure DocumentDB - MongoDB - MySQL - Neo4j - OrientDB
  • SQL Data Management: MySQL
  • Tools: MySQL Workbench
  • Other: Agile