The Fish Face project is in its final phase, and the first Fish Face unit has now been successfully installed on-board a fishing boat in Kupang, Indonesia! Amir from Refind struggled with everything from expected challenges like lack of electricity and internet connectivity availability, to more unexpected problems like cable-chewing mice and timing of the tide.
Since July the Fish Face Unit has been used at a local fishery site in Kupang to collect images of different fish species in order to build up a large database of the local fish species. Thousands of images have been collected and there is a first “classifier” installed now - able to recognise about 65 different fish species. This software will be updated continuously along with an increased number of collected images.
The Fish Face Unit was, as planned, installed on the deck on a local fishing boat. Deck space is very limited and so is the access to constant electricity or internet. We have solved this by adding a power supply and a cloud based data storage solution to which information can be uploaded when possible. The activity of classifying fish is not real-time dependant and can be performed when possible. The geographical location tagging will however be done at the actual time when the photo is taken, so the GPS data collected is not depending on internet access.
All classifications are stored with their species name and GPS tags, and we have also added the possibility to do quality checks by connecting to a webpage where the latest classifications can be viewed. This will give both fishermen and the staff of The Nature Conservancy a transparent and easy process to overview and improve the performance.
In the table above the classifications are listed and an image is shown from the actual Fish Face unit next to the label image of the classification performed. Later on a segmentation functionality will be added, where the fish length will be calculated. The system also allows for handling input from many different image sources (boats).
The next phase of the project will focus on evaluating the equipment and overall solution, and aim to expand the project into installing more camera units on more boats and expand the operations.
Meet us at Going Green - CARE INNOVATION 2018in the historic Schoenbrunn castle in Vienna on November 26-29!
The EU project sustainablySMARTwill organise sessions on “Circular Design of Mobile Devices” and “Smartphones: Repair, Remanufacturing and Reuse of Components” on November 29, 2018 as well as show several live demos during the Going Green conference.
In our project exhibition booth you can see demos of the Phones Sorter by Refind, test services by Grant4Com, component re-use by ITR and Semicon, the Puzzlephone prototype by Circular Devices, embedded modules by AT&S, Speech and Fraunhofer IZM, data erasure from Blancco and D4R tablet by MicroPro.
On November 30, we will have a live demo together with ProAutomation of the automatic sorting and disassembly of smart mobile devices during the Technical Excursion to ProAutomation´s facility in Vienna.
The rest of the conference program will feature the latest in circular economy, environmental design, clean manufacturing, resource efficiency, climate change, new eco-efficient technologies, collection, reverse logistics, refurbishment, carbon trading, re-use, recycling and policy making from leading experts in industry, academia, consulting, recyclers and public area around the globe. Leading companies and institutions in green electr(on)ics will present their innovative products, processes and services at the exhibition.
We are proud to announce that our technology is entering the southern hemisphere and more specifically Melbourne in Australia, where the leading Australasian electronics recycling company CMA Ecocycle is located. CMA Ecocycle are growing their business and are in the process of building a new facility, where the battery sorting process will take place. The OBS500 will be the first automatic battery sorting line installed in Australia.
“The automatic sorting is an important step for us to make the battery handling more effective, both in terms of sorting quality and direct costs”, says Doug Rowe, the managing director of CMA Ecocycle, “and it will enable us to safely handle our material, which we believe will increase in the time to come. We are happy to bring the latest advanced sorting technology to Australia with support from the government.”
CMA Ecocycle is originally a mercury recovery and recycling company, that handles lighting equipment, medical waste, electronic waste and batteries. The company has a high level of automation and always aims to work with state-of-the-art equipment to get the most out of the material.
For us at Refind, it is of great value to expand into yet another country and region of the world. However, it has also raised concerns in terms of maintenance availability and the battery database update, but we have seen the issues as opportunities by going straight at them. For example, we have now developed the scanning software so that most of the battery scanning process, that is needed for adding new batteries to the system, will be possible to perform by using the battery sorter.
The OBS500 will arrive to its new home in Melbourne towards the end of the year. The official opening of the new process line at CMA Ecocycle will take place in the 1st quarter 2019.
Swedish tech newspaper interviews our CEO Johanna Reimers about the third generation battery sorter. Click on the the image to read the whole article.
STATE OF THE ART BATTERY SORTING FACILITY
We are proud to present the successful installation of our new battery sorter, the OBS500, at the brand new facility of Batteriretur in Fredrikstad, Norway!
The shipping, installation and commissioning went smoother than ever before and it is very much thanks to the new space efficient design of the equipment. Less parts, less need for assembly, smaller footprint and more standardised packaging and testing has made the installation easier and better. During a couple of days the machine was installed, staff was trained and the sorting process up and running. This was followed by the final quality tests performed this week, showing the best sorting results ever!
It was a true pleasure to install the equipment at Batteriretur. They have made great efforts in building a new energy efficient battery sorting plant right by the waterfront in Fredrikstad.
THIRD GENERATION BATTERY SORTING
As you have heard in earlier posts, this step feeder design is the third generation of our sorting machines. We first used vibrating shaker boards and directional carpets to line up the batteries. It looked nice to begin with, but in the end it turned out to be quite challenging. If the batteries were dirty, the dirt stayed in the carpets and decreased the performance. For the second generation, we invented our own system, a series of V-belts and gravity as the speed accelerator. It was great in terms of speed and performance, but required quite a lot of space and used many moving parts.
We still wanted to build something that would be more space and maintenance efficient - and finally found a good sub-supplier and development partner to do this with by the end of 2016. After a lot of work and prototyping, we introduced the third generation - the step feeder - during the fall of 2017, which we now installed in Norway. It has a slightly lower throughput than the second generation, but we believe that in the long run this machine will be a winner - being more reliable and require less maintenance!
Here is a short movie showing the different feeding designs!
We are happy to announce our latest customer, AS Batteriretur, located in beautiful Fredrikstad in Norway. We have agreed to deliver the latest version of the Optical Battery Sorter, the OBS500 with the new step feeder functionality, in the beginning of April 2018! The OBS500 will be installed as one of several many new machines and equipment at the modern Fredrikstad facility, that is being partly moved into already, partly still being built by Batteriretur.
Batteriretur handles about 80% of the Norwegian waste batteries, and are making great investments in both sorting and processing technology for batteries, anticipating higher needs for battery recycling in a country where many of the vehicles have turned electric.
For us at Refind, it is our second Norwegian project, the first one was the Battery Refund Machine launched with Energizer at Coop Norway during the spring of 2017. We are happy that the Norwegians are eager to stay ahead of the latest battery related technology!
The OBS500 will be able to sort 500 kg of waste portable batteries per hour. The new feeding solution allows a smaller footprint as well as less parts, which facilitates shipping, installation and maintenance. We are excited to see the new machine in production during the spring!
And here is what the press is saying about this latest news!
The magazine Product Recycling News have written a nice article about the Optical Battery Sorter installation at Raw Materials Company in Niagara Falls, that took place in the early summer of 2017. Both Ashish Bhandari, the CTO of Raw Materials, and Johanna Reimers, the CEO of Refind, were interviewed. Read the article below or on the magazine online page!
We are happy to announce that we are launching the next phase of the FISH FACE project together with The Nature Conservancy! Until now we have verified that our software can handle fish species recognition by collecting fish images taken in a on-land fish photo booth. The next step is to design, build and install an on-board photo capturing device to be used on some of the small fishing boats of Indonesia.
The purpose of collecting the images and recognise them automatically is to understand the fish populations better by gathering information about the species, the age, the size and the geographical origin in a more efficient way. We work closely with The Nature Conservancy who are involved in many different fish-related projects - and hope to make a large impact on the fishing industry and fishing research by introducing artificial intelligence and automation. This phase of FISH FACE is planned to take about a year and will involve several field trips to Indonesia for testing and try-outs.
The new fish photo booth should accommodate fish sizes up to 80 cm long, and later on even larger fish. Given the rather rough conditions on these types of boats, the device must be robust and foot print efficient as well as not cause any extra handling for the fishermen. Quite a challenge - stay tuned!
We are pleased to announce that Coop Norway and Energizer have launched the world’s first battery reverse vending machine in Oslo, Norway. The event was held on Earth day, April 22nd, at one of Coop's stores.
The machine is developed by Refind Technologies and allows customers to return all types of household batteries in a similar way as a reverse vending machine for bottles. The customers will receive a discount of one Norwegian krone per battery in the form of a discount coupon that can be used when buying new batteries. We hope that this initiative will have a positive impact on battery recycling by increasing awareness and providing incentives for people to recycle household batteries.
This has been an incredible and unique opportunity for us at Refind; to develop the world's first reverse vending machine for batteries and our first consumer-focused machine/application. The main goal was to design a machine that is user-friendly and easy to understand for anyone who comes by with a battery to recycle. We know everything about recognizing and handling batteries, so the main challenge was to make it cost efficient, user friendly and precise. We therefore, focused a lot on the user experience when reading the display screen, interacting with the machine and receiving the printed coupon.
Highlights from the launch:
We have compiled the most frequently asked questions we receive from you. Hopefully, they provide some more insight into our operations.
1. What kind of objects are Refind's systems capable of identifying?
We have been asked to identify all kinds of objects: both crazy and normal stuff. Body parts in trash, coconut grading as the unexpected objects and used electronics and defects in furniture as more on the normal side. Important questions in return that we ask the customers are WHY (why automated and not manual) and HOW (how do you tell it apart), and then we weigh that against what different sensors would be able to perform.
2. What kind of sensors do you utilize?
We use all kinds of sensors and combine them on our technical software platform; the neural networks can use different sensors as data input sources. However, to have everything takes time and usually costs more than it is worth. Also, a limitation of sensors usually increases the processing speed. The most important sensor for our current applications is an RGB camera for taking images. We also use laser sensors for identification of sizes or location detection.
3. How do you select the right kind of sensors for each system?
The sensors are selected based on the material to be sorted. We can use material specific sensors (like NIR, X-ray, LIBS or something else that can only tell what material it is). This makes sense when you are dealing with objects with homogeneous material. There are many companies already doing this.
3.1 Following up on that, how does Refind differ from other companies?
We focus on objects with complex material structures, like whole products, used electronics, where a material sensor does not make sense. You need to understand what model something is for it to be useful information for the customer. Then a camera is the best thing.
4. What kind of camera do you utilize?
So far, we are doing fine with our RGB camera, but it is similar to a one-eyed person that cannot tell depth. By adding a 3D camera, we have basically added another eye, allowing for depth check, which makes a big difference for recognizing items in a co-mingling environment.
5. How does your classification system work?
A computer program is fed with images of known identity for example "this is a picture of a computer", it then learns what to look for in these images in order to correctly classify them. Once the system is trained, the learning process stops and it is used for real-time classification of the objects that are being sorted by our machines.
6. How accurate are the classifications?
It depends on how many images the system has got access to for training itself for the task. More images give better accuracy. The battery sorters produce fractions of 97 - 99% purity.
7. How many different kind of objects can you recognize? AND How many images do you need per object to be recognized?
The system can recognize as many objects as have example images of. The number of images needed is different depending on the objects and kinds of images we get, from 30 and up to several thousands depending on the object.
Do you have a question for us? Don't hesitate to email us at email@example.com or give us a call at 073-310 03 62.
We are proud to announce that we have been invited to speak about our recognition technology at the 10th International Illegal Unreportered and Unregulated Fishing Forum at the Chatham House in London on March 16-17.
Our machine learning expert Rasmus will present possibilities and opportunities within fish identification and learn more about the subject from the knowledgeable list of other speakers as well as from the audience.
Twice every year, we set aside a day to come together as a team, to discuss our past achievements and develop a road map for the future. The event has come to be known as "Refind Day". This year, we hosted Donnie Lygonis from KTH Innovation, who made a presentation about creativity. Here are some of the highlights from the event:
On January 31st, Refind was invited to Vinnova to talk about how to write a successful application for the Eurostars research program. Our CEO, Johanna Reimers, presented Refind and the SOMEWAIR project and how the application was done. This application was created together with DTI, Danish Technology Institute, with whom we are working closely with in the research project.
The application obviously went fine, the presentation was also OK and how is the project in itself going, you may wonder? Well, it is going very well. We are now developing our first movie recording scanning program, allowing multiple items to be added to the database simultaneously and continuously. This will also allow the classification of several items in parallel.
As usual, Refind will exhibit at the International Electronics Recycling Congress in Salzburg on January 17-20! New for this year is that our CEO Johanna Reimers will be speaking about our sorting technology in one of the seminars - the "Sorting technology" session on Thursday January 19th in the afternoon. Don't miss the speech called "Is More Technology Really the Solution to the Challenges within Circular Economy?".
Check out the entire program here.
Also new for this year is that we will bring our latest machine - a small desktop sorting unit including a robotic pick arm. As of now it can sort phones and fish - come and have a look at it in our booth!
Read about how our technology can be used to sort out what is valuable and what is hazardous in used electronics - and what different applications we are working with currently. All in Swedish!
Full article here.
We are happy to announce the sale of two OBS600 battery sorting machines to our new Canadian customer - Raw Materials Company! The first machine is to be delivered in May to their sorting facility close to Niagara Falls.
Raw Materials Company has more than 30 years of experience of collecting and recycling batteries. Their main market is the province of Ontario and they are one of the largest recyclers of batteries in Canada with increasing collection volumes every year.
For Refind, it is a strategic step to add yet another country to the list of installed base.
We are happy and proud to announce that the FISH FACE project won the People's Choice Award in the Google Impact Challenge Australia 2016! Since another project, the Great Barrier Reef Foundation, got as many votes as FISH FACE, Google decided to award both projects the extra 500 000 AUD funding.