In the dynamic landscape of retail stores, bars, clubs, and seasonal markets, the need for effective product visibility becomes even more evident. Illumination technologies are amongst the highly effective means for brand distinction and impactful visual communication. 

Introducing SaralOLED Label Ink set: A paradigm shift in OLED illuminated labels industry

In this episode, we discuss how MIT researchers tackle the problem of counterfeit seeds by using unclonable labels made of silk nanoparticles. These labels help ensure that farmers are using genuine seeds, preventing losses and maintaining the integrity of crops.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/b84075c2-bd3c-4a8f-b96b-c8dc6a2caa81?dark=false" class="fr-draggable" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> <hr>EPISODE NOTES(0:40) - <a href="https://www.wevolver.com/article/tackling-counterfeit-seeds-with-unclonable-labels" target="_blank">Tackling counterfeit seeds with &quot;unclonable&quot; labels 🌱🔐</a><hr>As always, you can find these and other interesting &amp; impactful engineering articles on Wevolver.com.To learn more about this show, please visit our<a href="https://www.wevolver.com/profile/the.next.byte" target="_blank">&nbsp;shows page</a>. By following the page, you will get automatic updates by email when a new show is published. Be sure to give us a follow and review on<a href="https://podcasts.apple.com/nl/podcast/the-next-byte/id1548255861?l=en" target="_blank">&nbsp;Apple</a> podcasts,<a href="https://open.spotify.com/show/6lPPsRtegnivsRUEsQ09R7?si=IPMiah7xT_apJtPjqvXMlA" target="_blank">&nbsp;Spotify</a>, and most of your favorite podcast platforms!

As a way to reduce seed counterfeiting, MIT researchers developed a silk-based tag that, when applied to seeds, provides a unique code that cannot be duplicated. Credit: Photograph courtesy of the researchers. Edited by Jose-Luis Olivares, MIT

In this episode, we discuss how MIT researchers tackle the problem of counterfeit seeds by using unclonable labels made of silk nanoparticles.

Podcast: Authenticating Seeds To 5X Crop Yields

<h2 id="isPasted">The Causes of Ongoing Problems for the Retailers &nbsp;</h2>A store&rsquo;s success depends on customer satisfaction and convenience while alleviating staff&rsquo;s frustration with repetitive, monotonous tasks. Retailers see in-store inventory and price management in need of optimization and improvement to deliver the convenience customers are asking for.&nbsp;<h3>Sources of the Retailers&rsquo; Price Accuracy Issues &nbsp;</h3>Taking into consideration that consumer-packaged goods (and especially retail) <a href="https://www.researchgate.net/publication/228269997_Do_Supermarket_Prices_Change_from_Week_to_Week" target="_blank">prices tend to change</a> frequently, labels displayed in-store need to adapt as fast as the modifications happen. Failure to present accurate pricing and promotions inconveniences customers&rsquo; buying journey. In correlation, shopping experiences poisoned by the inconvenience of inaccurate labeling lead to loss of business, which is never desired. &nbsp;&nbsp;Retailers have the responsibility to monitor if products are precisely named, marked with the correct price or if the right promotions are applied. Each label must be verified against the store&rsquo;s price and promotions database. Such processes are defined by repetition and monotony, heavily relying on staff, an excessive amount of time to be finalized, and continuous implementation. &nbsp;<h3>Sources of the Retailers&rsquo; Inventory Issues &nbsp;</h3>Stock and inventory management goes beyond a retail store&rsquo;s backroom and extends in front of the customers, on shelves. It is a multi-level process defined by a long communication chain that is prone to errors and delays. More than ordering and restocking, issues of the supply operations target trends and patterns, data collection, demand forecasting (dependent on store data), on shelf stock condition monitoring (misplacement, clutter, missing). &nbsp;&nbsp;Having overviewed the price and inventory issues retailers confront, let&rsquo;s explore existing solutions for their correction.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1664542497880-in+store+stock+and+prices.jpg" class="fr-fic fr-dii">In-store on-shelf availability and price labels&nbsp;<h2>Solutions Available to Retailers &nbsp;</h2>Solutions that solve problems of the supply chain are starting to get to the <a href="https://fitsmallbusiness.com/retail-statistics/" target="_blank">heart of the retailer</a>. Even though they approach shelf gap detection and in-store inventory data, monitoring on-shelf availability needs a more robust solution that tackles these issues holistically. &nbsp;&nbsp;The retail automation market is extensive, and there are three solutions that seem to be under retailers&rsquo; consideration more often than the others. &nbsp;<ul><li>Electronic Shelf Labels and Shelf Cameras &nbsp;</li><li>Autonomous robots &nbsp;</li><li>Semi-Autonomous robots &nbsp;</li></ul>Technologies such as Electronic Shelf Labels, to maintain price accuracy, and retail shelf-mounted cameras, to track product availability, are currently being deployed to physical stores to boost operational efficiency. &nbsp;<h3>Electronic Shelf Labels (ESL) as a Solution for In-Store Price Inconsistencies &nbsp;</h3>Electronic Shelf Labels are small units using <a href="https://www.eink.com/electronic-shelf-label.html?type=application&id=5" target="_blank">e-Ink</a> paper to display product data from price and name to stock availability or applied promotions. Being updated wirelessly and automatically from systems that centralize product information, ESLs serve retail operations concerning on-shelf price conformity. &nbsp; &nbsp;To populate a supermarket-sized perimeter with smart labels, a retailer must invest in thousands of individual shelf-placed units. However, ESLs have replaced repetitive tasks with others of the same nature. Labels are not scanned <a href="https://www.yardview.com/post/retail-benefits-and-disadvantages-of-the-digital-price-tag-is-electronic-shelf-labeling-esl-worth-your-time#:~:text=Electronic%20Shelf%20Labeling%20Training&text=Limited%20use%20of%20an%20ESL,leaving%20customers%20frustrated%20and%20confused." target="_blank">by hand</a>, but that doesn&rsquo;t prevent malfunctions of the electronic price tags. The printing and individual placement of paper tags is changed with a tedious <a href="https://retail-optimiser.de/en/electronic-shelf-labels-need-more-use-cases/" target="_blank">battery</a> or device replacement process, slowed down by difficult installation operations and expensive infrastructure costs. Additionally, as the store integration process of ESLs is highly dependent on the company they&rsquo;ve been acquired from, so is the maintenance process. &nbsp;&nbsp;On-shelf availability (OSA) refers to the products available to be purchased from a store, by customers at a given time. To monitor levels across the supply chain, retailers have slowly moved from manual audits to solutions based on <a href="https://easyflow.tech/next-generation-retail-analytics-how-to-improve-on-shelf-availability/#:~:text=On%20shelf%20availability%20(OSA)%20estimates,fast%20moving%20consumer%20goods%20analytics." target="_blank">artificial intelligence and computer vision</a>. One of those solutions is retail cameras for on-shelf availability.&nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1664542537340-Electronic+labels.png" class="fr-fic fr-dii">ESLs-Electronic price labels<h3>Shelf Camera Features for Monitoring In-Store Inventory / OSA &nbsp;</h3>From an operational point of view, shelf cameras do an excellent job when it comes to product and stock detection, compliance with product placement strategies, and data collection (inventory updates, shopping patterns). However, with shelf gaps being only one side of the problem, the retail shelf cameras build to high expenses and reliance on long communication chains prone to human error. &nbsp;<a href="https://eyrene.com/blog/how-to-track-shelves-in-retail-image-recognition/" target="_blank">Passive monitoring</a> of OSA does not refill shelves, solve labels&rsquo; accuracy issues or their replacement.&nbsp;Maintenance processes and costs for hundreds of devices do not justify the need for <a href="https://thegrocerystoreguy.com/what-day-of-the-week-do-grocery-stores-" target="_blank">total, constant surveillance</a> of products. The surge in product demand remains unpredictable and concentrated under the peak traffic periods of the shopping day or promotional campaigns. &nbsp;&nbsp;Retail OSA cameras not only require installation procedures that are lengthy and costly but also depend on the manufacturer across maintenance processes. From cables and mounting supports to network administration, and overall system setup and integration with the retail store, shelf cameras introduce supplementary tasks for which the staff needs to be rigorously trained.&nbsp;Having its focus only on-shelf availability and out-of-stock situations, shelf cameras are a solution that although popular still struggles to have their cost versus benefits validated by retailers. Complex integration processes and long adjustment timeframes for retailers and staff to operate the new system contribute to the <a href="https://www.industryarc.com/Report/20012/retail-camera-on-shelf-availability-market.html" target="_blank">impeded adoption</a> growth of OSA cameras. Retailers must be ready for a considerable commitment upfront and ongoing, as they are indirectly forced into vendor lock (training, store integration, updates, and maintenance are dependent on the manufacturer of the solution). They need to be prepared for changes brought to the store&rsquo;s infrastructure, already implemented software and solutions, and a different way of operation and specialized workforce demand. &nbsp;<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1664542596892-shelf+camera+view.png" class="fr-fic fr-dii" style="width: 467px;">Shelf camera viewESLs and shelf cameras are solutions dependent on human intervention, relying on interventions subsequent to the reported data. Hence, development in retail automation has taken a giant leap toward solutions that aim to function without the need for human help. &nbsp;&nbsp;Covering both price and inventory issues, autonomous robots have brought a new level of efficiency to in-store tasks as well as new problems and complexities that retailers have not been prepared for.&nbsp;<h3>The Complicated Transition to Autonomous Retail Robots &nbsp;</h3>Autonomous robots are used and are known for scanning a store for price tag inconsistencies, on-shelf inventory, and stock issues. Although bringing efficiency to OSA and price tag detection-related tasks, in-store problems are still not solved in their integrity (communication chains are still long and error-prone). Issues are detected and signaled but to actually replace a price label or replenish on-shelf stocks are actions still dependent on long, error-prone communication chains. &nbsp;The solution has been put into question, its utilization causing trouble in retail stores and not delivering the expected results. Consumers have had trouble adapting to the self-roaming robot attacking, getting scarred by or being hurt by its ROI issues, high acquisition and maintenance costs, together with the registered malfunctions, make retailers question fully autonomous solutions. &nbsp; Building bridges between solutions that are outdated, incomplete, and heavily reliant on staff intervention (ESLs and shelf cameras) and the farfetched, costly autonomous robots, semi-autonomous robots are collaborating with humans to deliver the best of both worlds.<h3>A Semi-Autonomous Robot Solves Multiple Problems &nbsp;&nbsp;</h3>With a semi-autonomous robot, the workforce required to execute tedious retail operation tasks is reduced to one staff member who oversees guiding the robot along the aisles and reviewing the output results of scanning sessions. &nbsp;The same operator can take action to resolve or communicate in-store pricing mistakes or out-of-stock issues. &nbsp;Most problems found during scanning can be resolved immediately, reducing the danger of misinformation or action delays by reducing the need for interdepartmental contact. Being semi-autonomous not only offers the advantage of being user-friendly (no specialized staff needed) but also more cost-effective than other solutions. The thing it needs most is to be brought from the charging station to the designated scanning start point. &nbsp;<h3>Introducing ERIS, the Semi-Autonomous Retail Robot &nbsp;</h3><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1664543413314-Printing+labels+on+the+spot.png" style="width: 581px;" class="fr-fic fr-dib">ERIS- on-the-spot label printing and replacement&nbsp;ERIS completes the functionalities of shelf cameras through additional capabilities and uses cases that treat OSA issues globally not partially. By being able to detect and scan both paper labels and e-ink electronic tags, the semi-autonomous robot makes the task of monitoring labels, including ESLs malfunctions, easier. As the shelves are scanned, when price tag issues are detected, the operator can print the correct labels and replace them on the spot or send alerts about the electronic tags that need to be updated. &nbsp;<h2>Takeaways &nbsp;</h2>In-store pricing accuracy and on-shelf inventory issues are on top of retailers&#39; minds when it comes to delivering convenience and satisfaction to customers. ESLs, shelf cameras, and autonomous robots have been overviewed as some of the most popular solutions considered by retailers. However, they have their own shortcomings when comparing the delivered results to the overall investment. &nbsp;&nbsp;Putting it into perspective, the semi-autonomous robot eliminates risks and concerns brought by its fully autonomous competitors while being a more complete solution than electronic shelf labels and shelf cameras. Human-operated robots like <a href="https://www.adaptarobotics.com/robots/eris/" target="_blank">ERIS</a> not only does it sponsor a better ROI, but it is also easy to integrate, maintain and get accustomed to solutions. &nbsp; &nbsp;&nbsp;

This article taps into discussing problems met by retailers and ways in which they can be solved with robotic automation.  

Robotic Automation for Brick-and-Mortar Retailers

This article was discussed in our <a data-saferedirecturl="https://www.google.com/url?q=https://www.wevolver.com/profile/the.next.byte&source=gmail&ust=1645483330039000&usg=AOvVaw3G1InVzNPFrh6EQN0Bd-pi" href="https://www.wevolver.com/profile/the.next.byte" id="isPasted" rel="noopener noreferrer" target="_blank">Next Byte podcast</a>.&nbsp;<iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless="" src="https://player.simplecast.com/5141d285-e7f7-4062-83fb-4e9e29407a6d?dark=false" class="fr-draggable" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true"></iframe>The full article will continue below.<hr>This article was first published on <a href="https://news.mit.edu/2022/invisible-labels-identify-track-objects-0128" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>.<hr>If you download music online, you can get accompanying information embedded into the digital file that might tell you the name of the song, its genre, the featured artists on a given track, the composer, and the producer. Similarly, if you download a digital photo, you can obtain information that may include the time, date, and location at which the picture was taken. That led Mustafa Doga Dogan to wonder whether engineers could do something similar for physical objects. “That way,” he mused, “we could inform ourselves faster and more reliably while walking around in a store or museum or library.”The idea, at first, was a bit abstract for Dogan, a 4th-year PhD student in the MIT Department of Electrical Engineering and Computer Science. But his thinking solidified in the latter part of 2020 when he heard about a new smartphone model with a camera that utilizes the infrared (IR) range of the electromagnetic spectrum that the naked eye can’t perceive. IR light, moreover, has a unique ability to see through certain materials that are opaque to visible light. It occurred to Dogan that this feature, in particular, could be useful.The concept he has since come up with — while working with colleagues at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) and a research scientist at Facebook — is called <a href="https://groups.csail.mit.edu/hcie/files/research-projects/infraredtags/2022-CHI-InfraredTags-paper.pdf" target="_blank">InfraredTags</a>. In place of the standard barcodes affixed to products, which may be removed or detached or become otherwise unreadable over time, these tags are unobtrusive (due to the fact that they are invisible) and far more durable, given that they’re embedded within the interior of objects fabricated on standard 3D printers.<a target="_blank"></a><iframe src="https://www.youtube.com/embed/Tjs1zH7IMxE?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" allowfullscreen="" class="fr-draggable" style="width: 767px; height: 430px;" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true"></iframe>Last year, Dogan spent a couple of months trying to find a suitable variety of plastic that IR light can pass through. It would have to come in the form of a filament spool specifically designed for 3D printers. After an extensive search, he came across customized plastic filaments made by a small German company that seemed promising. He then used a spectrophotometer at an MIT materials science lab to analyze a sample, where he discovered that it was opaque to visible light but transparent or translucent to IR light — just the properties he was seeking.The next step was to experiment with techniques for making tags on a printer. One option was to produce the code by carving out tiny air gaps — proxies for zeroes and ones — in a layer of plastic. Another option, assuming an available printer could handle it, would be to use two kinds of plastic, one that transmits IR light and the other — upon which the code is inscribed — that is opaque. The dual material approach is preferable, when possible, because it can provide a clearer contrast and thus could be more easily read with an IR camera.The tags themselves could consist of familiar barcodes, which present information in a linear, one-dimensional format. Two-dimensional options — such as square QR codes (commonly used, for instance, on return labels) and so-called ArUco (fiducial) markers — can potentially pack more information into the same area. The MIT team has developed a software “user interface” that specifies exactly what the tag should look like and where it should appear within a particular object. Multiple tags could be placed throughout the same object, in fact, making it easy to access information in the event that views from certain angles are obstructed.“InfraredTags is a really clever, useful, and accessible approach to embedding information into objects,” comments Fraser Anderson, a senior principal research scientist at the Autodesk Technology Center in Toronto, Ontario. “I can easily imagine a future where you can point a standard camera at any object and it would give you information about that object — where it was manufactured, the materials used, or repair instructions — and you wouldn't even have to search for a barcode.”Dogan and his collaborators have created several prototypes along these lines, including mugs with bar codes engraved inside the container walls, beneath a 1-millimeter plastic shell, which can be read by IR cameras. They’ve also fabricated a Wi-Fi router prototype with invisible tags that reveal the network name or password, depending on the perspective it’s viewed from. They’ve made a cheap video game controller, shaped like a wheel, that is completely passive, with no electronic components at all. It just has a barcode (ArUco marker) inside. A player simply turns the wheel, clockwise or counterclockwise, and an inexpensive ($20) IR camera can then determine its orientation in space.In the future, if tags like these become widespread, people could use their cellphones to turn lights on and off, control the volume of a speaker, or regulate the temperature on a thermostat. Dogan and his colleagues are looking into the possibility of adding IR cameras to augmented reality headsets. He imagines walking around a supermarket, someday, wearing such headsets and instantly getting information about the products around him — how many calories are in an individual serving, and what are some recipes for preparing it?Kaan Akşit, an associate professor of computer science at University College London, sees great potential for this technology. “The labeling and tagging industry is a vast part of our day-to-day lives,” Akşit says. “Everything we buy from grocery stores to pieces to be replaced in our devices (e.g., batteries, circuits, computers, car parts) must be identified and tracked correctly. Doga’s work addresses these issues by providing an invisible tagging system that is mostly protected against the sands of time.” And as futuristic notions like the metaverse become part of our reality, Akşit adds, “Doga’s tagging and labeling mechanism can help us bring a digital copy of items with us as we explore three-dimensional virtual environments.”The <a href="https://groups.csail.mit.edu/hcie/files/research-projects/infraredtags/2022-CHI-InfraredTags-paper.pdf" target="_blank">paper</a>, “InfraredTags: Embedding Invisible AR Markers and Barcodes into Objects Using Low-Cost Infrared-Based 3D Printing and Imaging Tools,” is being presented at the ACM CHI Conference on Human Factors in Computing Systems, in New Orleans this spring, and will be published in the conference proceedings.Dogan’s coauthors on this paper are Ahmad Taka, Michael Lu, Yunyi Zhu, Akshat Kumar, and Stefanie Mueller of MIT CSAIL; and Aakar Gupta of Facebook Reality Labs in Redmond, Washington.<hr>Reprinted with permission of <a href="https://news.mit.edu/2022/invisible-labels-identify-track-objects-0128" id="isPasted" rel="noopener noreferrer" target="_blank">MIT News</a>"

MIT scientists built a user interface that facilitates the integration of common tags (QR codes or ArUco markers used for augmented reality) with the object geometry to make them 3D printable as InfraredTags. Credits: Photos courtesy of MIT CSAIL.