ESR13: Using truck sensors for road pavement performance investigation

Hey crew, Are you alright? Are you ready for reading a new post? Alright, let’s start then! Almost a month ago I started my secondment in Microlise Ltd . As I already mentioned in the past: Microlise is one of the two companies that is involved within my project. They are experts in truck fleet management and they collect and analyse data from large truck fleets for helping their customer in maximising utilisation, increasing efficiency, and improving economy and safety for their fleets. Fig.1 – The Microlise Ltd logo. How is it going here in Microlise? Well, I have to say that working in the company has pros and cons. The cons are mainly related to the timing: I have to wake up at 6:00am every morning and it takes 1 hour-ish by bus to get to  Eastwood, where Microlise is located. Then, I go back home very late (sometimes I come back home after 6:30pm). Fig. 2 – No crew, it is not that terrible! ;) This means that quite often I’m tired, and that

Hey crew! Are you ready for a new post?! Here we go then! Today I’m going to introduce you to a more technical topic. In fact, we are going to talk about machine learning and Artificial Neural Networks (ANNs) in particular. Machine learning is a subfield of computer science which aims to give computers the ability to do something without being explicitly programmed for doing that. Originally, it comes from the study of pattern recognition and computational learning theory in artificial intelligence. Exploring the study and construction of algorithms that can learn from experience (historical data), the algorithm operates by building a model from example inputs in order to make data-driven predictions or decisions. ANN is just a branch of Machine Learning. They are data processing paradigms inspired by the way the biological nervous system process information in human beings (Biological Neural Networks, BNNs). Usually they are used to estimate or approximate functions t

Hey crew! I’m sorry for not writing sooner but I was quite busy with work first and then I finally went on holidays for a while. But finally, here we go: I’m back! Today I’m not going to talk about any technical stuff (I have some news about that, but I will share it someother time ;)). I guess that a more relaxed topic is probably much better to catch your attention after holidays. I hope you all are doing well and that you had the opportunity to spend some time at home with your family, in the mountains, or at the seaside as I did. You know, sometimes we deserve some relax! We need to spend some time with friends, with our family, go for holidays, and also why not, we could play Pokemon GO… Are you telling me that you haven’t ever heard about Pokemons (short for pocket monsters) and Pokemon GO? Are you kidding me, or what? It is the phenomenon of the moment! It is basically a free augmented reality game for smartphones (it is available for both iOS and Android operat

Hey crew! I have great news for you: I published my first scientific paper! Yep, guys that’s amazing! It happened last week, during the 8 th RILEM International Conference on “Mechanisms of Cracking and Debonding in Pavements” in Nantes (7-9 June, 2016) . It is about part of the work I did in EMPA for my Master Thesis. For this reason, I’d like to say thanks to my ex-Supervisors Prof. Gabriel Tebaldi - who was my Professor in Italy when I was studying at the Universit à degli Studi di Parma – and Dr. Martin Arraigada, Dr. Christiane Raab and Prof. Dr. Manfred Partl - who were supporting me during the internship. The title of the paper is “Influence of SAMI on the Performance of Reinforcement Grids” and you can find it here if you want to have a look on it. The paper was presented by Dr. Christiane Raab at the beginning of the afternoon session during the first day of the Conference. What about the first real academic conference I participated to?

Hey crew! I hope you all are doing well and welcome back to my blog! Today I’d like to give you feedback about my experience at Microlise Transport Conference (just Conference in the following). It is a conference about road transport organized every year by Microlise Ltd and its sponsors in order to spread knowledge about the issues and solutions that nowadays affect the industry. No, I haven't presented any article and I hadn’t any presentation there. Come on crew, there were people like Her Royal Highness the Princess Royal presenting at the Conference – and I don’t know what about you but, at least for me, it was the first time in my life I saw a member of the Royal Family in person. Actually, it was the first time for my Supervisor too. However, the Conference was really good and it was basically the opportunity for me to deeply understand the issues nowadays faced by the road transport industry. Personally, I think that the most impressive thing I got f

Hello everybody! I hope you spent nice holidays and you came back to work cheerful and full of energy! Today, as promised, I’m going to explain a bit more about the data we collect and about the type of analysis we intend to perform. As I previously explained , the objective of the project is: to assess the relationship between truck fleet fuel consumption and road pavement conditions. Data about the fuel usage are collected by Microlise Ltd whilst data about road pavement conditions are collected by TRL Ltd (but owned by Highways England ). In both cases, data are stored in very big databases which can be remotely queried whenever needed. This study is going to consider only data about trucks travelling along the English SRN (Strategic Road Network). The SRN is completely managed by the Highways England authority. It is around 7’000 kilometers long and is mostly made of motorways and ‘A’ roads. Although the SRN network represents just 2% of the length of all roa