In November 2019, the Bundestag passed the climate package, which, among other things, aims to renew the German cycling infrastructure. In order to gain an overview of the current condition of cycling paths, conventional road condition monitoring usually requires expensive measuring vehicles. In the field of data science consulting, we as a company have been dealing with topics such as sensor data analytics and predictive maintenance for several years. Consequently, we have asked ourselves how these topics can be combined cost-efficiently to evaluate road conditions. This would be of particular interest to local authorities who could use rental bike fleets equipped with this setup.
The goal of this project is an automated bicycle-based road analysis kit which entails no monitoring tasks for the cyclist. Therefore the data of an acceleration, gyroscope and GPS sensor has to be transmitted to a classification server. Different machine learning models will be compared to each other, aiming for the highest possible accuracy in predicting road type and condition. A distinction is made between the road types tarmac, cobblestone and gravel in conjunction with the conditions smooth, rough and bumpy, resulting in a total of nine classes. Furthermore, the results will be visualized live on a map using an IoT platform.
The setup in this project requires two things in particular: data and a machine learning model. We collect the data sets ourselves, so that the issue of hardware selection for sensor data recording plays an important role. Regarding the classification task different models are tested, from tree-based procedures to deep learning approaches.
The Bosch XDK 110 was chosen for sensor data recording (see middle picture in fig. 1). It is equipped with an accelerometer and a gyroscope, among other sensors. The recorded data can be transmitted wirelessly via Bluetooth, WiFi or SD card. The freely programmable buttons and LEDs serve as a simple user interface. The XDK can be programmed in C using the Eclipse-based XDK Workbench. Furthermore, a normal trekking bike is used (picture top left). The XDK’s bracket, which also serves as rain protection, is mounted in the bike’s basket (bottom left picture). To annotate the collected data, a labelling app was developed using the React Native framework (see pictures on the right). The recorded data of the XDK is transferred to the app via Bluetooth. Moreover, the app uses the smartphone’s GPS sensor to determine the current position. When a route has to be annotated, the plus button is pressed to enter the corresponding information.
By these means a first data set is created: Over a period of 376 minutes, 91 km are covered and about 735,000 readings per sensor channel are recorded, resulting in a sampling rate of 32.5 Hz. The average speed was about 14.6 km/h. To assess the influence of the sampling rate on the accuracy of our models, a second data set was created, in which the sampling rate was to be maximized. For this purpose, the data can no longer be transferred to the labelling app via Bluetooth due to lower throughput. Instead, it is stored directly on the SD card. The buttons and LEDs of the XDK were programmed accordingly for labelling and for starting and stopping the recording. Finally, the second data set covers a distance of about 77 km, which was recorded in 314 minutes. Due to the higher sampling rate of 294 Hz, significantly more data was recorded – about 5.6 million data points per sensor channel. Finally, a test data set was recorded in the same way, except that the bicycle was replaced with a kvv.nextbike to check the transferability of the models to unknown bikes. A total of approx. 9 km were driven, with just over 500,000 measured values stored per sensor channel.
For the machine learning part, different models were compared. On the one hand, tree-based methods such as Random Forest and XGBoost as well as Support Vector Machines were chosen. All these methods have already proven to be very reliable models for a wide range of classification tasks. In addition, tree-based algorithms are quite intuitive and their decisions can be interpreted easily, as opposed to black box models. On the other hand, deep-learning based methods have been used. In addition to LSTM networks, convolutional neural networks were tested, especially deep residual networks. We want to take a closer look at these.
Figure 2 above shows a ResNet developed by Fawaz et al.  for time series classification. Compared to image recognition, there is a peculiarity here: The filters slide over the input data only in one dimension (time). Everything else however works just the same. We see three residual blocks, each containing three convolution layers. The first block uses 64 filters and the other two blocks use 128 filters. The residual connections can prevent the degradation problem, i.e. deeper nets can be built without a rapid loss of training accuracy. Finally, the residual blocks are followed by average pooling and a fully connected output layer.
With InceptionTime, the current state of the art in the field of time series classification is proposed by Fawaz et al.  too. The architecture remains largely unchanged compared to the ResNet before. However, only two instead of three residual blocks are used. Lastly, the individual convolution layers are replaced by inception modules (see figure 3 above). In these modules, parallel convolution operations are running, whose output is merged to a common output.
The models are implemented using Python, scikit-learn and keras. A grid search with tenfold stratified cross-validation is performed for hyperparameter optimization. Prior to this, the input data used by the models are prepared by normalizing them. In addition, summary statistics such as averages, standard deviations, etc. are calculated for the non deep learning based methods. A total of 14 new features per sensor channel serve as input for these models.
With regard to the first data set, the two deep residual networks ResNet and InceptionTime were able to achieve the highest validation accuracy, with both achieving around 77%. The lead over the next best model (CNN-LSTM) is 7%, all other models are below the 70% mark. However, all models have difficulties in recognizing certain classes, and confusion often occurs. Two exemplary sequences of such problem classes can be seen in the lower left picture (fig. 4). In the upper left picture you can see a sequence of rough tarmac, in the lower left picture of rough cobblestone. On the x-axis the time steps are shown, where 200 time steps also correspond to the sequence length of a model input. The y-axis represents the acceleration in x-direction. In both cases the values fluctuate in a similar range, and the period lengths are also almost identical, so that the classes cannot be distinguished from each other easily.
A closer look at these classes led to the assumption that a higher sampling rate may be able to improve accuracy. With the recording setup of the first dataset, a sampling rate of roughly 32 Hz was achieved. The average velocity was 14.6 km/h or about 4.05 m/s. So on average a measurement was taken every 12.5 cm. This seems quite infrequent regarding e.g. the size of a cobblestone, which can be much smaller. Also road imperfections can occur more frequently. Consequently, the second data set was created with a maximized sampling rate. Again, two sequences of the former problem classes are shown (top right image in fig. 4). This time only the x-axis is adjusted. Since the sampling rate is increased by a factor of 9, the axis comprises 1,800 time steps. Now it seems that the two classes can be distinguished more easily since a measurement is taken on average every 1.36 cm. To sum up, the increased sampling rate has proven to be the key success factor. All models were able to achieve a significantly higher validation accuracy; the residual nets even reach values around 99%.
Furthermore, the transferability of the models to another bicycle should be checked, which is why the third data set was recorded. It can be noted that the data deviates quite strongly from the second data set. The standard deviations of the gyroscope values sometimes differ by a factor of 3 to 4 compared to the training data. Consequently, the models trained with the second data set cannot make reliable predictions. That means before enrolling this project in a larger scale with many bikes recording data some setups such as bike type (especially suspension) and tire pressure have to be assured.
In the end, the setup for real-time visualization of the sensor data was realized. The architecture of the test setup is shown in figure 5 below. The XDK is mounted on a bicycle as before and can transmit the accelerometer and gyroscope data wirelessly using the WiFi hotspot of a smartphone. At the same time, the GPS sensor data of a smartphone is recorded by a corresponding app. Both the smartphone and the XDK publish their data on a public Mosquitto test server. The MQTT protocol is used, a publish-subscribe protocol for typical IoT tasks. With this setup, the XDK can achieve a sampling rate of about 250 Hz, while the GPS coordinates are updated whenever the position of the smartphone changes by more than five meters. On the other side there is a computer that performs the classification and visualization. This has an intermediary program running with a Mosquitto broker who subscribes to the channels (topics) of the Mosquitto test server on which the sensor data are published. Then InceptionTime is used to classify the data. After that the intermediary publishes the classification results including the corresponding coordinates on a channel to which the Thingsboard-MQTT- Broker has subscribed. Thingsboard is an open source IoT platform that enables the recording, processing and visualization of sensor data as well as the management of sensor devices. It is operated on the local computer in form of a docker container. The XDK and the intermediary have been registered in the platform in order to be able to manage them. Finally, the subscribed sensor data are visualized in a dashboard.
The picture below (fig. 6) shows the dashboard, which was created in Thingsboard. There, the current position is drawn in a map with a marker. Furthermore, the tooltip shows the coordinates and the classification result. In addition, the driven route is drawn in black. Next to the map, a table is shown in which the last data received is recorded over a period of five minutes.
To sum up, it is challenging but absolutely possible to perform a street classification task like the one presented in a low cost and fully automated manner. Therefore the usage of state of the art machine learning algorithms led to very impressive classification results. Thus, a model suitable for real world use could be created – especially in connection with the automated transmission, classification and visualization of the data.
Moreover, some lessons for future ventures in the field of sensor data analytics could be learned from this project. In particular the sampling rate plays an important role: At the very beginning of such a project the question should be asked at which minimum frequency interesting information can be expected.
Finally, to use this proof of concept in practice, only a few adjustments need to be made. When collecting training data, different bikes should be considered or at least the type of bike that is to be used in production. Ideally the data should be recorded by different cyclists. Otherwise, what has been considered in this project applies as well: Consider as many different routes, air pressures and speeds as possible.
: Fawaz, H. I.; Forestier, G.; Weber, J.; Idoumghar, L.; Muller, P.-A.: Deep learning for time series classification: a review. Data Mining and Knowledge Discovery 33/4, S. 917–963, 2019.
: Fawaz, H. I.; Lucas, B.; Forestier, G.; Pelletier, C.; Schmidt, D. F.; Weber, J.; Webb, G. I.; Idoumghar, L.; Muller, P.-A.; Petitjean, F.: InceptionTime: Finding AlexNet for Time Series Classification. arXiv preprint arXiv:1909.04939/, 2019.


In this post we will be looking at setting up our Raspberry Pi in an automated fashion so that we can install Apache Airflow and some other tools to automate key parts of our workflow.
Purchasing a Raspberry PiI recommend the Canakit Raspberry Pi 4 4Gb Starter Kit.
It contains everything you need to get a complete setup going quickly, and it is available for a very reasonable price.
The kit contains:
- The Raspberry Pi 4 itself (with 4GB of RAM)
- A 32GB SD card, preloaded with a bootloader (no fussing about flashing the drive yourself)
- A minimal, but attractive case
- A cooling fan and additional heat sinks for the CPU, RAM and GPU chips
- A USB type-C powerswitch adapter (actually quite useful)
- AC Power adapter (to USB type-C)
- A 4K compatible micro-HDMI to HDMI cable
Setting up the Raspberry Pi & Operating System
Here is a Youtube video I’ve put to together explaining how to assemble and setup a Canakit Raspberry Pi 4.
Choosing a configuration tool
- Resource intensive (due to Ruby)
- Ruby syntax
- Solo and server-based architecture
- Industry leading
- Solo and server-base architecture
- Easy to learn
- Has lost favour in recent years
- Hard to learn
Has great Terraform support.
Less resource-heavy which is important on a Raspberry Pi.
SSHing Into a Raspberry Pi
By default you can log into the Raspberry Pi via SSH credentials like so:
Then when prompted for a password, you can enter the default password of
This may also be set to your admin password if you changed that after installation. If it is still the default, this password should be changed immediately.
If you need help setting your SSH password, you can read more here.
You can also look into setting up a *.local domain name to make things easier if you’d like.
Installing Ansible on a Raspberry Pi
Here we install some required packages (
dirmmngr), add a PPA which gives us a more recent version of Ansible. Then we add keys for this new PPA, update our local apt, then finally download and install the latest Ansible.
echo "deb http://ppa.launchpad.net/ansible/ansible/ubuntu trusty main" \ | sudo tee -a /etc/apt/sources.list sudo apt-key adv \ --keyserver keyserver.ubuntu.com --recv-keys 93C4A3FD7BB9C367 sudo apt-get update sudo apt-get install -y \ ansible sshpass dirmngr ansible --version
Installing Ansible on Our Local Machine
Now on our local machine, we should also ensure we have Ansible installed.
On MacOS I can do this simply using
and running the command
brew install ansible.
Other installation methods are available here.
Then let’s create our hosts file (inventory) so Ansible knows where to find our Raspberry Pi.
# Run this in a terminal on your local machine sudo mkdir /etc/ansible sudo nano /etc/ansible/hosts
Enter the following configuration.
# /etc/ansible/ansible.cfg [defaults] inventory=./hosts
Note: You can also update your Ansible configuration to look in the local directory for the inventory file. This will allow you to have multiple projects using different configurations in the future. Read how here.
Setting Up an SSH Key on the Raspberry Pi
First of all you will need to generate a SSH key key which is usually found in your home directory at the following location. If you do not have one of these keys you can learn how to generate one here.
Next will need to copy our public key to the raspberry pi using the following:
ssh-copy-id -i ~/.ssh/id_rsa.pub firstname.lastname@example.org
You should then be asked to enter your raspberry pi’s SSH password, and should copy your public key onto the device. This will mean that when logging in from your current machine, you should no longer require a password.
This means that Ansible also will not require a password.
Setting Up a Basic Ansible Configuration
Here I’m going to define my Raspberry Pi as the shorthand “pi”, add it to a group called “automaton” and add a variable to all hosts within that group.
# /etc/ansible/hosts [pi] email@example.com [automaton:children] pi [automaton:vars] cy_automaton=true
Now let’s test our configuration so far by running a command on our Raspberry Pi remotely.
ansible pi -a ls
You should see a directory listing of your Raspberry Pi’s home directory.
In a followup post we’ll be looking at installing Apache Airflow and other automation tools on the Raspberry Pi using Ansible.
This will allow us to automatically publish blog posts, tweets, and by doing nothing more than dropping a file in a directory.
Stay tuned, and as always, take it easy kittens!


AI and machine learning have long been a bastion of data scientists. But if AI is to go mainstream in the Enterprise, we need to get developers in on the game too. With offerings like Azure Cognitive Services, the Bot Framework, and the advent of Automated Machine Learning (AutoML), that is starting to happen. And with the array of sample notebooks and other learning materials, even “manual” ML is becoming accessible to a wider range of tech professionals. What can we do to accelerate the onboarding of developers into the AI world? And, when we succeed, what will the role of the data scientist be? Join this panel of experts to hear their views and ask what they think is coming next.


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Recently, the 1CSI team was delighted to feature in the Maxon regional and Global blogs. Maxon built the the depth-rated high-precision motors used by our flagship subsea inspection system, TIAMAT.
Our next-generation alternative to traditional ultrasonic inspection techniques, TIAMAT is a portable, compact, easy to deploy system, developed to provide reliable, multi-phase array ultrasonic subsea inspection. From the beginning, we have focused on increasing the quantity and quality of inspection data collected on a normal run. For a sneak peek at TIAMAT in action, read our blog post from 2021 or visit the NZTC YouTube channel.
Smooth, frictionless motion
Maxon has provided precision DC micro motors since 1961, powering ‘humanoid robots and in high-precision industrial applications, in tattoo machines, passenger aircraft, camera lenses, race cars, and cardiac pumps’.
In the interview, Matthew Kennedy, CEO of 1CSI Ltd said: “The motors are absolutely crucial, because scanning demands smooth, frictionless motion… While the phased array transducers are collecting data, movement of the carriage needs to be seamless and repeatable, including when scanning a changing diameter asset. We chose maxon because their motors give us the precision we need.”
Maxon zooms in on the benefits of ROV inspections
In their blog, the Maxon team explore the world of subsea inspections and how micro motors are supporting the next generation of ROV instection systems; “From oil & gas installations to submarines, structures operating in deep sea conditions need regular inspection. Remote operated vehicles (ROVs) make this process much safer and less expensive, and they rely on scanning technology, which is crucial to data collection. Precise motion control is helping… achieve highly accurate inspection with the fastest-yet speeds of data collection.”
If you’d like to read the Maxon blog post in full, visit their website here.


PHP is a server-side scripting language designed primarily for web development but is also used as a general-purpose programming language. Originally created by Rasmus Lerdorf in 1994, the PHP reference implementation is now produced by The PHP Development Team.
ASP.NET MVC is a web application framework developed by Microsoft, which implements the model–view–controller (MVC) pattern. It is open-source software, apart from the ASP.NET Web Forms component which is proprietary.
Microsoft SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network (including the Internet).


Markus Bänziger, our dear friend from Switzerland who’s an electrical engineer volunteered to come and make sure all the electrical work that has been done by a local electrician will be safe for running a hospital. I’m afraid I’ll be doing injustice in trying to describe what all he has been installing, as my understanding of electrical work is utterly poor. But what I know is he brought two suitcases of cables and special earth leakage circuit breakers and voltage surge protection devices, and spent three weeks working on the hospital and our parents’ house “the Altersheim” ensuring we won’t be surprised by electrical surges that might ruin all our equipment, kill us or burn down the hospital. He also helped instal the main line for the power supply to the hospital, so finally there’s light in the building! We are so grateful for his exceptional work here!


Prototype development is one of our company passions. We can help you from concept to creation by filling in the unknown requirements, researching the market, and leveraging our background working for startups to deliver an amazing solution.
Our team can help you through any part of your project or take you through the entire thing from start to finish. We are here to help you realize your goal. Past projects include:
- On soldier power management devices
- Fuel cells in fixed wing unmanned aircraft
- Smart vehicle electronics for work trucks
- Home brewing systems
- Break away bumpers for delivery trucks
- Delivery vehicle concepts
- Consumer beauty products
We find the right solutions, technology and manufacturing, to meet your target market.
Treetown Tech’s team of software engineers brings a diverse set of capabilities. With decades of experience in embedded software development and testing, we can help you on your next project.
- Model based design (Matlab/Simulink)
- Real-time operating systems (RTOS)
- Control algorithm development
- CAN, LIN, Flexray, I2C, SPI, RS232
End of Line Testing and Manufacturing Equipment
Treetown Tech’s electrical engineering team has a full range of experience developing hardware, from one off prototypes to fully production hardened electronics. We can help you with your next electronics project in automotive, military (ITAR), or consumer electronics.
- PCB/PCA design
- Analog / Digital / Mixed-Signal
- Power Electronics
- World class fully digital buck/boost converter design
- Digitally manipulated analog converter technologies
- Maximum Power Point Tracking (MPPT)
- Brushless and Brushed motor/generator drives
- Energy Storage
- Lead acid
- Automotive standards
- RF Design
- Bluetooth low energy
- Sub-1 Ghz
- System on a Chip (SoC) Simulation
- System C
- Transaction Level Modeling (TLM)
If you have a problem requiring advanced design and analysis, we have years of experience in
- Control theory
- Thermodynamics & Heat Transfer
- Finite Element Analysis
- Vehicle Dynamics Simulation
- Unmanned arial / ground vehicles
- Military hardened equipment
- Thermal management
Who We Are
We bring On Demand Innovation with the intersection of engineering, design, and market analysis.
Treetown Tech specializes in high tech product development. Each member of our team has years of experience working in startups on cutting edge technologies. With a key focus on products advancing alternative energy, we have designed fuel cell systems, custom high efficiency dc-dc converters, brushless motor controllers, battery chargers, and many other products.
Our team of electrical, software, and mechanical engineers would love the challenge of creating solutions to meet your needs.
At least! We don't really count them
Helping us create your solutions faster
from small tasks to multi-year projects


Mobile App/Tablet Design, UI/UX
As our modern world becomes more and more digitised, it's not going to take long for every home to be digitised too. Some of the more expensive places being built today already have prototype system designed into them and below is a system I helped design for a technology company based in America.
The system needed to be clean and straight forward to have operating software that easily works over various devices and also can be re-designed easily for different branding. From wireframe layouts of all the parts needed, we researched interface OS designs on the market today. The end result is a simple and elegant system that has software available for mobile, tablet and wall interfaces.
You can control the window and door locks, camera systems, check the weather, change the temperature and turn on lights. All of which can be done from inside and outside the house through whatever device you have to hand. This is the default design for the system, but we also came up with some example variations for a couple well known US companies.


ThinWire Ethernet MAU (10Base2) Internal slot O PBXDC-DA PBXDC-DA PBXDC-DA PBXDC-DA
The AlphaStation 255/233 and 255/300 Desktop Workstations comprise a
family of entry to mid-range PCI-based Alpha Universal Client systems. The
AlphaStation 255 family delivers premium performance while providing access
to thousands of applications running on the DIGITAL UNIX, OpenVMS or
Windows NT Workstation operating systems.
The AlphaStation 255/233 system uses the Alpha 21064A microprocessor
running at 233 MHz with performance measuring 4.27 SPECint95 and 5.09
SPECfp95. This entry level to low end system is ideal for running 2D CAD,
CASE, Multimedia and Software Development applications.
The AlphaStation 255/300 system also uses the Alpha 21064A microprocessor,
but at a higher speed of 300 MHz and with performance measuring 4.23
SPECint95 and 5.81 SPECfp95. This mid-range system is optimal for working
with 2D CAD and 3D CAD applications.
All AlphaStation 255 systems come packaged in a compact enclosure, with
capacity for up to 512 Mbytes of parity memory, 128-bit wide memory bus, four
storage slots, four option slots (2 PCI, 1 PCI/ISA combination, 1 ISA) and a
1 Mbyte secondary cache. The high performance PCI I/O bus, running at 132
Mbytes/second, provides expansion for options such as high-performance
graphics, networking, and SCSI adapters without the need for additional tabletop
options or expansion boxes. All systems support a wide variety of industrystandard
peripherals and PCI/ISA options. Other standard features include
integrated Twisted Pair Ethernet (ThinWire is optional), stereo-quality audio,
external ports for serial/parallel communications, and external SCSI.
The AlphaStation 255 Family workstations come in a new design


Disposing of electric bulbs correctly
We use electric bulbs every day. However, we rarely ask ourselves how to dispose of an electric bulb correctly. This article contains tips for the environmentally friendly disposal of electric bulbs, low-energy bulbs and other lights.
In Switzerland, around 120,000 tonnes of electrical and electronic equipment are recycled every year, including around 1,000 tonnes of lighting of various types: traditional electric bulbs, LED and low-energy bulbs, and so on.
To ensure that even more lighting can be recycled in future, this article tells you how to dispose of electric bulbs correctly.
Why you should recycle lighting
Modern lighting contains numerous components that can be recycled. These include glass and rare elements such as indium and gallium. If these components are recycled, fewer resources are required to produce new lights.
Some lamps contain toxic substances such as mercury, which in the worst-case scenario can cause health problems if disposed of incorrectly. In Switzerland, incorrect disposal can also result in a fine of up to several hundred francs.
One tonne of recycled electrical and electronic equipment (e.g. lighting) offsets the environmental pollution caused by a 247,500 kilometre train journey. This is the equivalent of travelling the entire Swiss rail network 48 times.
Which lighting can go in your household waste?
You can dispose of the following lighting in your household waste:
- Traditional electric bulbs
- Halogen lamps
The following lighting must not be disposed of in your household waste:
- Fluorescent lamps
- Low-energy bulbs
- LED lamps
Disposing of all your lighting correctly
Traditional electric bulbs can simply go in your household waste. Never put them in your glass recycling bin, as it is very difficult to separate the metal filament inside the electric bulb from the glass.
Halogen lamps are also made of glass and metal. So you can dispose of them in your household waste. Never put them in your glass recycling bin.
Fluorescent lamps contain mercury. So you need to take them to a suitable collection point. Don’t worry, this doesn’t involve any extra effort. These collection points are often located in supermarkets such as Migros or Coop. They will accept your old fluorescent lamps free of charge.
LED lamps and lights, such as LED strips or LED panels, must be disposed of at a collection point. Although these lights do not contain any harmful substances, they do contain valuable, recyclable components. If you put LED lamps in your household waste, these will be lost.
Low-energy bulbs contain mercury and should also be taken to a collection point.


A chip containing millions of genetic variations that are common in Africa could help scientists bring the benefits of precision medicine to the continent. The chip could lead to new insights into human health as well as new treatments that work better on Africans. Its developers say it will be ready to use in early 2017.
“This will be the first chip that has been created to specifically target genetic variation in African populations and people of African descent,” says Nicola Mulder, a bio-informatician at the University of Cape Town in South Africa who led the work on the chip. The chip will contain 2.5 million different markers hand-picked for their African relevance. It’s been produced by the Human Heredity and Health in Africa (H3Africa) initiative, a program to boost genetic research in Africa funded by the UK and the US. The program has collected tens of thousands of samples from Africans to study genetic links for diseases like diabetes, sleeping sickness, rheumatic heart disease and tuberculosis. Read more details at http://bit.ly/2ftVHw6


airGR version 22.214.171.124
Latest developments of the airGR rainfall-runoff modelling R-package: composite calibration/evaluation criterion and improved snow model to take into account satellite products
We now have a new website for airGR: https://hydrogr.github.io/airGR/
The whole list of changes is available here: https://hydrogr.github.io/airGR/NEWS.html
Parsimonious and simple lumped rainfall-runoff models are useful tools for research and engineering. From years of experience, the Hydrology Group at Irstea (Antony) developed the GR models suite. Aiming at providing an open source tool, the team started to develop an R package (R Core Team, 2018), named airGR (Coron et al., 2017, 2018), that contains these simulation models (including the GR4J model). The airGR package permits to run six hydrological models dedicated to different time steps (hourly to annual), one snow accumulation and melt model (CemaNeige), one automatic calibration procedure, pre-defined graphical plots and a set of efficiency criteria.
It is now possible in airGR to use a composite calibration/evaluation criterion that combines several criteria as a single criterion. The choice of the different criteria and the weight applied to each one can be adjusted according to needs. This possibility can improve the calibration performance of models by considering several objectives.
Furthermore, several studies have shown that the use of snow cover area (SCA) observations from satellites, such as MODIS SCA, can improve snow model calibration. The airGR package now proposes an improved version of the semi-distributed CemaNeige degree-day model that better represents the hysteretic relationship between SCA and snow water equivalent (SWE). This modification coupled with the combined calibration of the CemaNeige and GR models on SCA data and on river runoff data significantly improve the simulation of the snow cover area by the model and give more robust calibrated parameters (Riboust et al., 2019).
Thanks to its success (about 15,000 downloads so far), the airGR development team carries on its efforts to improve the code, offer new features and improve the documentation. Recently, the development team also released a new package, airGRteaching (Delaigue et al., 2018), which depends on airGR and has expressly been developed for educational purposes, in order to avoid the difficulties that students may have with R programming.
Coron L., Thirel G., Delaigue O., Perrin C., Andréassian V. (2017). The Suite of Lumped GR Hydrological Models in an R package, Environmental Modelling & Software, 94, 166-171. DOI: 10.1016/j.envsoft.2017.05.002.
Coron L., Perrin C., Delaigue O., Thirel G., Michel C. (2018). airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 126.96.36.199. URL: https://webgr.irstea.fr/en/airGR/.
Delaigue O., Coron L., Brigode P. (2018). airGRteaching: Teaching Hydrological Modelling with GR (Including a Shiny Interface). R package version 0.2.3.2. URL: https://webgr.irstea.fr/en/airGRteaching/.
R Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/.
Riboust, P., Thirel, G., Le Moine, N., and Ribstein, P. (2019). Revisiting a simple degree-day model for integrating satellite data: implementation of SWE-SCA hystereses. Journal of Hydrology and Hydromechanics, 1, 67, 70-81. DOI: 10.2478/johh-2018-0004.


Red Tacton: NTT and 'Human Area Networking'
Trust the Japanese to use human bodies as conduit for network transmissions.
Japanese company Nippon Telegraph and Telephone Corporation (NTT) claims to have developed the first viable Human Area Network (HAN) device, enabling fast data transfer between devices using the human body as a conduit.
NTT reckons this latest advance on the wireless Personal Area Network concept — dubbed RedTacton — can transmit data over the surface of the skin at up to 2Mbps. Where it differs, though, from previous offerings, is that a RedTacton-enabled device does not have to be in direct contact with the skin — only within about 20cm. NTT explains the technical background:
RedTacton can also "transmit" through clothing or shoes, allowing the useful possibility of downloading MP3s through a floor-based sensor while dancing the Lambada. What's more, you can swap files by straight human contact, so two filesharers equipped with RadTacton devices can indulge in torrid illegal P2P activity and have sex at the same time.
But apart from that, why bother with RedTacton when Bluetooth can already do the job wirelessly? With Bluetooth, it is difficult to rein in the signal and restrict it to the device you are trying to connect to. You usually want to communicate with one particular thing, but in a busy place there could be hundreds of Bluetooth devices within range.
Besides, humans apparently make poor aerials, something which is good for security because even if you encrypt data it is still possible that it could be decoded, but if you can't pick it up it can't be cracked.
NTT says it is committed to "moving RedTacton out of the laboratory and into commercial production as quickly as possible by organizing joint field trials with partners outside the company". There's more technical info available here.
Microsoft last year patented a system for "transmitting power and data using the human body". It's based on the IBM concept, but MS sees the technology being used primarily for power, rather than data transfers.


- State of the art technique for localizing and mapping an environment in real time using both camera and LIDAR sensors by fusing visual features and LIDAR data to estimate robots movements with higher precision.
- Implemented a robust real-time ROS-based framework for accurate trajectory estimation, 3D Mapping, and Localization by fusing stereo RGB image and LiDAR data using ICP in a non-linear optimization framework to achieve an ATE of 1.773m
- VLOAM used feature extractors such as ShiTomasi, ORB, BRIEF, FAST etc. The descriptor matching was done using Brute-force, L2-Norm and FLANN based matching.
- Augmented the feature extraction and matching algorithm with Super-Point descriptor and SuperGlue matching algorithm.
Full Report Here


ficonTEC designs and produces high precision production equipment for the assembling or testing of components.
Automation Solutions in Microsystems
ficonTEC Service GmbH is an innovative high-tech company that has rapidly established itself in a highly specialized market. Our technical competence, world-wide contacts and importantly the will to understand our customers and to find individual and optimum solutions together make us a competent business partner.
We are the market leader when it comes to automated assembly or test of micro-optics or opto-electronics such as laser diode manufacture, medical technology, security and defense engineering, as well as telecommunication. We develop off the shelf and individual automation solutions in microsystems engineering that increase the efficiency and precision of your production processes.
The core team at ficonTEC consists of engineers from the specialist fields of optics, electrical engineering, software development, and mechanical engineering. These developers are supported by technicians with a variety of skills.


The WAGO Group is an international, family-owned company that offers both market-leading products for electrical interconnection technology and an open automation platform recognized across all industries. Automation users of WAGO profit from the freedom of being able to implement automation and IT tasks on an open platform while having access to a nearly boundless range of input and output modules. End users also profit from ready-to-use and custom tailored coordinated solutions. Benefits include enormous versatility, design freedom and end-to-end communication, from the sensor level all the way up to the cloud. Users also enjoy a high degree of reliability – even under extreme conditions. WAGO products connect, measure and network through simple solutions and intelligent connections. Customers profit from scalable solutions for integrating physical measured variables and from applications and assets in fields such as building automation, energy management, shop floor connectivity and much more. WAGO is open and ready for your digital future.
Find out more now!


See the world from inside out...
ducted reconnaissance drone optimized for first responders and emergency operations
Digital Aerolus introduces the Aertos 121™, a ducted drone optimized for emergency response teams.
First responders require hardware with a unique set of characteristics: emergency response equipment must be reliable, rugged, rapid to deploy, simple to operate, and provide cost-effective solutions for demanding tasks in potentially dangerous situations. The Aertos 121™ from Digital Aerolus delivers.
Folded Geometry Code (FGC™), a flight control and operating system constructed upon the same advanced flight mathematics used in space navigation, equips the Aertos 121™ to fly reliably and smoothly time after time – even when no GPS signals are present. When seconds matter, your emergency team can rapidly deploy, pilot the aircraft safely from a remote location, and observe the target environment with a broad field of view using the integrated FVP (first person view) camera and telemetry system. Bright LED illumination makes sure that darkness is no problem.
Digital Aerolus designed its Aertos drones with technologies that address the real-world challenges of police, fire, and emergency responder departments. The Aertos 121™ drone – an invaluable member of your critical response team.
First responders & emergency teams
Ducted fans – 120mm duct
FPV (first person view) camera
20 x 20 x 4.5
508 x 508 x 114
The AERTOS 121™ maximizes versatility and ruggedness in a nimble, maneuverable package. Protected blades and a ducted fan design enable your UAV to predictably complete your mission objectives even in harsh or challenging conditions – indoors and out.
Aertos 121™ Market Sheet
.pdf format; last updated 5/19
A rugged ducted drone optimized for emergency teams and first responders surveying challenging environments
Manholes and sewers
Carbon fiber frame
Ducted fan propulsion
180° vertical camera control
Does not require GPS
(photo and features may change…)
Digital Aerolus Drones Deliver Six Key Features
Stable indoor and outdoor, even in GPS-challenged areas. Predictable flights indoors and out – even if the UAV strikes an object.
Safe ducted & protected-blade designs reduce risk and prevents injury to your workforce, and damage to nearby objects and even the UAV itself.
Simple to start, simple to launch. Deploy rapidly – from carrying case into your airspace in a matter of seconds.
High-resolution video telemetry and still images – with broad visual view both horizontal or vertical – even in darkness.
Rugged design and strong materials means that Digital Aerolus drones can handle your challenging day-to-day work environment.
Compact designs – the perfect tools for tight and confined spaces and places other drones can’t even imagine going.


Where Ideas are Born
When Trelleborg Sealing Solutions decided that it was time to move its Stuttgart headquarters, creativity was a focus. Not only would its new location be a great place to work but it would also be a great place to think.-By Donna Guinvan
BACK IN 2016, TRELLEBORG SEALING SOLUTIONS SIGNED A CONTRACT for a new building in Stuttgart, Germany, to house the business area’s global headquarters, its German headquarters and various global support departments. And right on schedule personnel began moving in ready for the official opening of the Innovation Center in September 2018.
- Trelleborg Sealing Solutions has moved its global headquarters, German headquarters and global support to the new Innovation Center in Stuttgart, Germany
- Research and development capabilities extended by 50% to 3,000 meters, with a showroom area
- New digital capabilities accelerate innovation and shorten development cycles
Prof. Dr. Konrad Saur
Accelerating Technological BreakthroughsWithin the Innovation Center, Trelleborg Sealing Solutions has extended its research and development capabilities by 50%, to around 3,000 square meters, including a 300 square meter showroom area dedicated to the department and demonstrating all R&D capabilities.
“Innovation is not only about new products and materials, but advancements in analytical and technical capabilities to support problem resolution and to accelerate technological breakthroughs,” says Prof. Dr. Konrad Saur, Director Global R&D at Trelleborg Sealing Solutions.
The new Trelleborg Sealing Solutions Innovation Center will host laboratories with the latest analytical equipment and measurement centers, next to innovation and prototype facilities, as well as a major test area with a fully equipped tool room and materials laboratory. The capabilities will range from standard and advanced mechanical testing, to advanced thermal and thermodynamic analytics, including Thermal Gravimetric Analysis (TGA), Digital Scanning Calorimetry (DSC) and Fourier Transform Infrared (FTIR) spectroscopy, to highly advanced analytical technologies such as a high-resolution Scanning Electron Microscope (SEM) with an Energy Dispersive X-ray (EDX).
“With such capabilities working in combination, complex problems in research, innovation, engineering and customer service can be assessed and brought to resolution rapidly.”-PROF. DR. KONRAD SAUR, Director Global R&D at Trelleborg Sealing Solution
An integrated approach“With such capabilities working in combination, complex problems in research, innovation, engineering and customer service can be assessed and brought to resolution rapidly,” Konrad continues. “No time is lost shipping samples from lab to lab, turnaround times and iterative assessment are enabled as crossfunctional competencies work directly together. These capabilities support material and product development efforts, fundamental research of sealing designs and interactions in sealing systems, as well as root cause and failure analysis in production and from the field.”
Konrad points out that, “Ever shorter innovation cycles, simultaneous engineering and increased complexity in new systems characterize the innovation process in today’s industry. To respond to this, product development and engineering are increasingly using digitalized information to make the processes faster and support cross-functional team work along the value chain.”
At the Innovation Center, Trelleborg Sealing Solutions will support its internal innovation processes, custom development and engineering through a fully digital development process that goes from 3D CAD to Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD) to 3D printing, as well as rapid prototyping. There will even be CAM-integration, where CNC machining information can be dropped into the tool room for tool or even product prototype machining.
WORK AND LIVE“The new building incorporates a ‘Work and Live Space’ concept, offering a perfect environment for our processes and project work,” says Carsten Stehle, General Manager of Trelleborg Sealing Solutions in Germany. “This, as well as improved transparency, will speed up and facilitate easy internal and external communications, allowing us to spend more time on partnerships with customers and suppliers. In addition, according to our Corporate Social Responsibility guidelines, the building will exceed the latest environmental standards.”
New Innovation Center
Digital will be key“We’ll be utilizing a full digital chain, supported by physical sampling, testing and analytics,” continues Konrad. “This will allow quick iterations and significantly speed up product development and engineering processes without information loss, multiple-data entries and data re-generation. 3D scanning for quality control will provide immediate feedback into design and prototyping.
“This capability will allow us to interact in a unique way with our customers that will accelerate innovation, shorten development cycles, reducing the number of designs and prototypes required to come to an effective final specification. With the new and integrated capabilities in our Innovation Center, Trelleborg Sealing Solutions will continue to make major steps in exceeding our customers’ expectations. We intend to be there for our customers always.”
THE FOURTH REVOLUTIONDr. Johannes Kunze von Bischhoffshausen, Manager Digital Transformation and Internet of Things at Trelleborg Sealing Solutions, says: “Diagnostics and prediction of seal health have long been a dream of engineers at Trelleborg Sealing Solutions. Industry 4.0 and the Internet of Things (IoT) are therefore becoming an important focus for manufacturers worldwide. There is a call for products to become smarter and more intelligent to reduce downtime, lower maintenance costs, create safer applications and reduce waste.”
Under the Cognitive Sealing concept, Trelleborg Sealing Solutions is rapidly building up expertise in this area, focusing on critical sealing applications. This is not just built upon unique Trelleborg assets, such as test rigs, but also in close collaboration with selected customers. In addition, the company is also piloting IoT technology to offer smart services and to increase efficiency and quality in manufacturing.
“We had to take a different approach to kick off the IoT initiative that is based on an open innovation philosophy and close collaboration with customers, startups, and research institutions,” explains Johannes.
A home to developAt the new Innovation Centre there will be a IoT Lab in order to give a home and an inspiring work environment to all IoT based initiatives. The lab will contain a prototyping area for electronics, as well as an IoT test rig and demo area.
“The purpose of the lab is to evaluate IoT technology and build prototypes in a very short timeframe,” continues Johannes. “Instead of a long theoretical conceptualization phase, we will start building prototypes as early as possible. Our IoT solutions are based on four pillars: innovative sensor technology, edge computing, and artificial intelligence – in conjunction with our e xpertise in the geometries and materials of advanced sealing solutions.
“We know that the opportunity to utilize IoT to accelerate the performance of our customers is virtually infinitesimal and we hope that the new lab will be one small step in grasping the huge potential that exists.”
INNOVATION IN ACTIONAs Konrad Saur said, innovation is not only about new products and materials, but advancements in analytical and technical capabilities. One case in point was a recent investigation undertaken by the R&D Team.
A customer noticed damage in the form of black particles on the inside surface of their hydraulic cylinder that they believed was caused by abrasion of the seal on the inner of the cylinder. Analysis on the inside of the cylinder and the particles was performed using an Energy-dispersive X-ray Spectroscope (EDS). In fact, the particles had nothing to do with abrasion by the seal but a high concentration of oxygen that had resulted in the buildup of rust.


Rear digicam choices embody EIS, Nighttime shot, Sluggish movement, and Portrait. By using optics, the Oppo F19 Pro is claimed to have a quad rear digicam setup that will embody a 48-megapixel main sensor, an 8-megapixel secondary sensor with a particularly-in depth-angle lens, a 2-megapixel portrait sensor, and a 2-megapixel macro shooter. The oppo f19 comes with a punch-hole cutout for the selfie digital camera, triple cameras organized in an sq.-digital digital camera module with a 48MP most important sensor, an in-show fingerprint sensor for security, and Prism Black and Midnight Blue colors. On the entrance, there is a sixteen MP camera with an f/2.4 aperture for selfies. As far because the cameras are concerned, the Oppo F19 on the rear packs a triple camera setup that features a 48-megapixel principal digital camera with an f/1.7 aperture; a 2-megapixel digital camera with an f/2.4 aperture, and a 2-megapixel digicam with an f/2.Four aperture.
The first rear digital camera is 48MP, and it comes with an 8MP large-angle lens, a 2MP depth sensor, and a 2MP macro lens. The OPPO F17 Pro has a quad-camera setup that features a 48MP primary sensor, an 8MP broad lens, a 2MP mono lens, and a 2MP depth sensor. More of a treasured addition to the already profitable F-collection smartphones from OPPO, the F19 Professional is loaded with options. The report additionally confirmed that the company would start teasing the smartphones starting subsequent month itself. The Oppo F19 Professional Plus is priced at Rs 25,990, and the Oppo F19 Pro begins at 21,490. Both smartphones will go on sale via Amazon. Above what the Narzo 30 Pro has to supply.
If a telephone seems 15,000 INR above the price and doesn’t provide an extra advanced frame price, it can decrease the consumer expertise. The phone is expected to incorporate 6GB RAM/ 128GB of internal storage. Together with the 6GB RAM and Adreno 610 GPU put in within the OPPO A53, it additionally affords commendable outcomes. AMOLED display with a 20:9 facet ratio, and an octa-core Qualcomm Snapdragon 662 SoC, paired with Adreno 610 GPU and 6GB of LPDDR4X RAM. The telephone will even perform with triple rear cameras. The telephone didn’t lag. The Oppo F19 will succeed the Oppo F17 launched final 12 months whereas the oppo f19 Skilled generally is a adjust to-up machine of the Oppo F17 Skilled.


Are you interested in signing up for a fixed line NBN service but do not know what to expect? For the previous several years, Australia has been working on building the national broadband network (NBN), which would permit every house in the country to connect to a fast and reputable Web connection. Currently, Internet speeds are quick in city places, but as you move away from city centres, connection drops also.
NBN aims to solve this problem so that even in remote areas can enjoy reliable Internet coverage. The NBN utilises an upgraded communications facilities which change old copper wires with fibre optics. According to reports, NBN satellite is presently being rolled out throughout Australia, enabling more individuals to experience advanced technology in Web connectivity.
There are some types of NBN Internet Service plans in Australia a family can get, and the purpose of this short article is to discuss the very first one– the NBN fixed line.
As the name recommends, the fixed line NBN operates utilising a fixed line where the signals are transferred from the source to the getting households. This NBN service is also called NBN Fibre because the signals are transferred using fibre optic cables.
This particular cable is amongst the most sophisticated means of signal transfers today. Unlike the old copper wires of the past, fibre optic cable televisions are comprised of glass and use light to transmit signals and information. Fibre optic lines can considerably increase Internet connection, and alter how people take a look at Internet browsing.
Here are some advantages of getting the fixed-line option from NBN Internet providers:
Can transmit data over far away without sacrificing excessive quality.
Is not impacted by sound and ground vibrations, which suggests a loss of signal is highly unlikely.
Can support high bandwidths of information transfer.
As you can see, the NBN fixed line is undoubtedly the next generation of Web connection in the nation. If you have an interest in acquiring it, inquire now with your nearby NBN suppliers to discover if NBN fibre covers your location.


Computer + Network Services
Tech can be a huge source of frustration when it doesn’t work.
Together, we can work it out.
Specialising in computer installation, problem-solving, fault rectification and system maintenance, Aspiring offers full-service computer and network support.
Whether you need a new set-up or fresh solutions, we’re here to help.
Take the stress out of IT with:
- Pre-purchase advice
- Installation and set up (including Internet, email, software)
- Fault fixing
- Upgrades and improvements
- Hardware (including printers, scanners and backup)
- Wireless and wired networking
- Mobile phone optimisation and set up.


Loris FicheraLoris Fichera
Will move to another country for work.
I've been programming Erlang since 2008, when I learned the basics @ University, I've done both my BSc and my MSc thesis on it.
Been an active member of the Robotics Team of the University of Catania (UNICT-TEAM) since 2008, (almost) all of our robots have Erlang onboard, so I have a quite good experience of what's like to run Erlang on embedded systems.
Professionally, I have recently been working for Jurma, a small italian company, where I was the mantainer (and, also, one of the main developers) of a PV monitoring system based on Erlang.
I am an effective team player. I love challenges.
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Willett Kempton is Professor in the College of Earth, Ocean, and Environment, and Technical Advisor for Special Initiative on Offshore Wind, at the University of Delaware. He is co-founder and Associate Director of the Center for Research in Wind. He is Affiliated Professor at Danish Technical University.
Dr. Kempton directs about 10 professional researchers and graduate students in research on clean energy technologies. He lectures widely and publishes scientific and technical articles on offshore wind power, electric transportation, and energy analysis. Kempton created the concept of using electric vehicles to provide grid services, and has four patents for technologies integrating electric vehicles with the power grid. He has also led ground-breaking analysis and policy recommendations on the cost of offshore wind power and on new deployment methods for offshore wind turbines. See URLs https://crew.udel.edu/v2g/ and https://crew.udel.edu/wind-power/ or twitter @WillettKempton