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“Digital Transformation Project – [HWL sample app]” TEAM 91

Introduction

Het Waterlaboratorium (HWL) is an independent partner in research and consultancy for drinking water, industry water and wastewater. In the Netherlands, every organization with a (drink)water facility is legally obligated to execute certain water quality tests. These rules apply for a broad range of different sectors. For example, HWL visits hospitals and pools, but also ships and drilling rigs. The reason for the quality checks of the water is the possibility for diseases in the drinking water like legionella. HWL carries out analyses of all types of water and advises on water treatment. HWL does this on commission and in cooperation with partners in the water chain authorities, knowledge institutions and enterprises.

Currently, the fieldworkers convert the collected data manually into the Laboratory Information Management System (LIMS). This system processes the samples to see if there are any deviations. According to the employees, this way of work is old-fashioned and needs to be modernized.

Current business

The testing process includes two teams of employees, the fieldworkers and the laboratory workers. Planning activities and the administration are done at the headquarters in Haarlem. The fieldworkers pick up their routes and paperwork every morning at that location. From there on they carry out the multiple test through the country. During the day they fill in the test results on the lists they picked up that morning. The fieldworkers return the lists and collected test results at the end of each day to the head branch in Haarlem. Thereupon the laboratory workers take over and examine the retrieved data. They manually put in the data into the LIMS. This program reports whether it finds any deviations. In other words, it states whether the test results are within the accepted interval. The laboratory workers draft a report in order to present their findings to the client and the fieldworker. Whatever the outcome of the test, the fieldworker returns to present the results. The fieldworker will retake a sample and/or shutdown the water supply system. The total process time is approximately two days, although deviations measured by the LIMS may extend it.

Description new technology

As tablet technology continues to improve, it offers a lot of opportunities to the traveling fieldworkers. Therefore, our solution for HWL to solve their issues is to integrate these tablets into their working process, as well as providing them with an app. The user-friendly tablets simplifies the fieldworkers activities and enable them to access information on the road. We deliberately chose tablet over mobile phones because of the user-friendly screen size and attractive appearance. The tablets demonstrate an innovative spirit when visiting the clients. Our solution was partially based on the improved accessibility to the mobile internet.

The HWL sample app

The HWL Sample app communicates through an API to the online bridge database. The app requests data and posts data to through the API. The online bridge database is leading, which means that the app has to sync its local database with the online bride database. The app also supports offline mode i.e. when the app is being used without an active internet connection, the saved data is stored in the local database of the app. All offline saved samples are stored in the local database in a queue table. This queue contains all the data that has not been posted to the server. The user can either manually send the items in the queue list to the server, or they will be automatically sent when the user save sample data with an active internet connection.

Analysis of the new technology

To give a quick impression of the strengths, weaknesses, opportunities and threats of the new technology, we conducted a SWOT analysis.

Strengths	Weaknesses
·         Quick response time ·         Time saving ·         Cost reduction ·         Ease of use	·         Battery life of the tablets ·         Total dependency on the hardware
Opportunities	Threats
·         Extension to mobile phones ·         Expansion potential	·         Slow adaptation ·         Possible vulnerable to hacking ·         Competitors creating a similar sample app

 

Conclusion

With all this in mind, we recommend the management of ‘Het Waterlaboratorium’ to implement the proposed solution to the IT problem. It is important that the application can be used by all the fieldworkers in order to reduce ‘time wasting’ and to fasten the response time of LIMS. This analysis supports the idea of introducing tablets and a HWL sample app because it will improve employee satisfaction, it will increase the efficiency per employee and also decrease the labour costs.

Tim, Roland, Wim & Tiziano

 Group 91

 

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Robotics is a fast developing industry. Developments in this industry again and again make our life easers with new applications. Nowadays, robots are becoming more advanced and are they able to take over tasks humans would normally perform. This leads to profound automation. At the same time, a discussion has started about how far robotics can and should go. Is it responsible to use robots? Mistakes made could be crucial, because sometimes human lives depend on it. We can state that the revolution of robotics has begun, and that there is no way back.

These days robots are being used for a wide variety of tasks. From drones in the army to very accurate incisions during operations in a hospital and from robots on planet Mars to self-driving lawnmowers, we see robots everywhere. Robots can work very efficiently and accurately and where humans have to take a break to rest or eat, robots don’t have to. The world is used to life with robots and we can state that we can’t do it without robots anymore.

The expectation is that there will be very intelligent robots in 2030, who are even capable of making decisions on their own. (Veltenaar, 2015). At the moment the prediction is that in 2050 robots are as intelligent as humans. This brings us to the other side of the developments. A robot will lead to a decrease in employment because it is cheaper and it can work 24 hours a day. The balance between capital and labour will be disrupted by robotics. Wealth will especially end up at the rich and the highly educated people. (Technologische Ontwikkeling, 2014) (Wetenschap, 2015) (z24, 2014)

The big question is how far robots will take over the world in the future. I think that technology will take over the humans and that there might be no turning back. If in 2030 robots will be more intelligent than humans and will make decisions on their own, a chance exists that they will take the wrong decisions. The moment an algorithm is written, there is no way to turn it off. One won’t know what this algorithm is planning to do, because it lives a life on its own once it is written. There might be a chance robots attack humans of that they want to have control over our lives at some point. If this really turn out to be so, humans will turn out to be robots, controlled by the robots. The fact that robots do not have feeling will not stop them from taking over the world or have mercy with humans.

The application of robots in the army are concerning. Nowadays, drones help in warzones like Syria to provide more safety, without the risk that human soldiers get hurt. However, if robots will be more developed they could possibly be a danger themselves. An army of robots that can make their own decisions can turn out pretty horrible. Ground wars will be decided on which country has the best robot army and more developed war robots will only lead to bigger wars.

My vision is supported by Elon Musk. This is the CEO of Tesla Motors and market leader in the industry of electrical cars, as well as the founder of SpaceX. Elon Musk is worried, he said ‘Science has to be very careful if robots are going to be connected to humans. We have to worry that we should not be tempted to do something very stupid’. In another interview he said ‘artificial intelligence could be more dangerous than a nuclear bomb’. This all sound very extreme, but it indicates that robotics has a downside as well. (Musk 2014)

This vision may be a slightly exaggerated kind of nightmare, but still humans have to be aware of the robots we are creating. I still think that robots will make our lives much easier, because there are also many good applications of them. For example, the home care robot which makes live of the elder people in the society much easers. This robot is a rollator, a reminder and many other functions in one. What do you think robots turn out to be?

 

‘Ruud Veltenaar’ (2015) accessed on 10/8/2016 via http://www.ruudveltenaar.nl/robotica-technologie-in-actie/

‘Technologische Ontwikkeling (2014)’ accessed on 10/8/2016 via http://www.technologischeontwikkeling.nl/robotica/ontwikkeling-robotica-biedt-nederland-kansen
‘Wetenschap’ (2015) accessed on 10/8/2016  via http://wetenschap.infonu.nl/techniek/144129-de-nieuwe-technologie-een-zegen-of-een-vloek.html
‘z24’ (2014) accessed on 10/8/2016 via http://www.z24.nl/ondernemen/asscher-automatisering-en-robot-zorgen-voor-toekomstige-werkloosheid-500074

 

 

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Big data analytics and pro sports are no longer strangers to each other. Nowadays, players wear accessories like the Adidas miCoach, a device that tracks everything a player does during a game from registering the heartbeat of players to the amount of steps taken. For a long time, people argued that hockey was resistant to the kind of data analytical models that were used in for example baseball. Hockey was too fast of a game compared to baseball with its stately pace. Players go on and off the ice about every 30 seconds while the game is still in play. If you thought data analytics weren’t coming to the NHL, you were wrong. (Olavsrud, 2015)

The National Hockey League, or NHL, is the biggest league of hockey in the world. It consists of 30 team based all over the United States and Canada and big money is made with starting salaries of 900.000US$ to the maximum of about 15.000.000US$. The general managers of NHL teams use data analytics for different purposes.

The first reason for data analytics is the players’ on ice performance. The first major system used is called Corsi, named after former goaltending coach of the Buffalo Sabres Jim Corsi. This so called Corsi is essentially the number of shot attempts (it is the sum of blocked shots, missed shots and shots on goal). This stat should indicate the approximate puck possession of a player. This stat show for example how well an individual player is doing, the higher the number the more your team possesses the puck, which usually leads to scoring chances. It can also be used the other way around, by showing how many shots your team gets against, when a player is on the ice. (Olavsrud, 2015)

Another reason for analytics is during contract negotiations with players. When the contract of a player expires, the general manager and representatives of the player get around the table to discuss new the new contract. Both parties are trying to convince the other party that they belong a certain contract, based on data. (Brousell, 2014)

Most recently, the youngest general manager in NHL history, John Chayka, was hired at just 26 years old. Once a promising young winger, whose career ended because of a back injury, Chayka focussed on data analytics for hockey. He began at a hockey school registering all data by hand. As time went on Chayka was introduced to multiple NHL teams and players who were impressed by his skills. Right now Chayka is general manager of the Arizona Coyotes, that he wants to make a data analytic franchise. Everything, from contract negotiations to on ice performance, will be analysed. (Sportsnet, 2016)

The revolution of using data in hockey has taken a huge step last year. I think more team are going to focus on using big data for every aspect there is in hockey. Only time will tell.

References:

Brousell, L. (2014) ‘8 Ways Big Data and Analytics Will Change Sports’ [accessed 5 Oct 2016] http://www.cio.com/article/2377954/data-management/data-management-8-ways-big-data-and-analytics-will-change-sports.html

Olavsrud, T. (2015) ‘NHL seeks to grab fans with data analytics’ [accessed 5 Oct 2016] http://www.cio.com/article/2901264/data-analytics/nhl-seeks-to-grab-fans-with-data-analytics.html

‘Coyotes’ John Chayka: the NHL’s answer to Mark Zuckerberg’ (2016) [accessed 5 Oct 2016] http://www.sportsnet.ca/hockey/nhl/coyotes-john-chayka-nhls-answer-mark-zuckerberg/