Set of Five Miscellaneous Requests

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Laundromat Payment Tech

It is increasingly common to see customers opt for technologically based payment systems. In fact, a current survey demonstrated that only 11% of the populace lean towards utilizing cash for purchases. This holds true in the laundry industry where many laundromats are adopting technologically innovated cashless payments systems, that include the PayRange Inc. mobile innovation solution that enables customers to pay through their phone, SpyderWash credit card payment system, and other card payment systems.


Laundromats who had previously used a coin exclusive payment system are now installing card payment systems from reputable companies, such as ESD, Card Concepts, and USA Technologies to provide customers with a more convenient and safer method payment alternative to the outdated coin or cash-based payments.
PayRange Inc., a leader in mobile payment innovation for machines, has produced an innovative solution that enables laundromats operators to upgrade existing machines within 2 minutes to accept mobile payments. The PayRange payment system is available for Speed Queen and Maytag machines. Jetz Service recently roll out PayRange's new technology in the Midwest. "We especially like the eureka feeling PayRange has provided to make Jetz feel like we are stretching our wings in what we see as a truly transformational application of technology in our space," said Scott Schenk, the Chief Financial Officer for Jetz Service Co., Inc.
SpyderWash System in conjunction with USA Technologies’ ePort Connect platform provides laundromats customers with an innovation that enables contactless, credit or debit mobile payments.
The SpyderWash Payment System was created in 2009 and allows laundry customers the option of using coin, credit or debit cards, a loyalty card, RFID contactless credit cards, or NFC Mobile Wallets to pay for their laundry on the machines with the system.


There are numerous technologies and apps that enable laundromats to operate technologically based payments systems. These include
mobile apps using Bluetooth technology and secure digital wallet that makes it possible for customers to pay for their phones without a credit card. One such app is LaundryPay, coming soon to Android and iOS. LaundryPay will allow the user to track machine availability
giving the customers the ability to plan their laundromat visit. In addition, the customer can pay through the app. Finally, the app provides smart notifications with wash notifications by LaundryPay.

Laundry monitoring systems- these systems enable the operator to keep tabs on the exact measurement of water usage, electricity and payment history etc.


PayRange Inc. mobile innovation solution, SpyderWash credit card payment system, and other card payment systems are some technologically innovated cashless trends that assist the customers of laundromats to pay at their convenience, either at the point of service or "contactless" by using either card payment systems or mobile app systems.
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AI in Industrial Supply Chains

Industrial supply chains are being revolutionized by the application of new technology, in particular AI which can “learn” from and assess massive amounts of data in order to optimize the various steps in the supply chain including prediction of product demand, warehouse network optimization, preventative maintenance of transport vehicles, and optimization of transport routes.


As AI technology matures, with increasing capability and commercial viability, it has been predicted that for the transport and logistics sector AI could “improve performance over other analytics techniques by 89%”. AI, often in combination with other technological advances in data analytics and IoT technology, is capable of automating or streamlining many processes across supply chain and logistics operations. The expected benefits from the application of AI on industrial supply chain operations are far-reaching, spanning “cost reductions through reduced redundancies and risk mitigation, improved forecasting, faster deliveries through more optimized routes, [and] improved customer service”.
The application of AI in supply chains, in particular transport and logistics, is expected to have a massive positive effect in terms of efficiency and savings, with a McKinsey report published this month (April 2018) predicting that supply-chain management and manufacturing as the industries with the greatest potential for AI, along with sales and marketing. The estimated financial impact on the supply-chain management and manufacturing industry combined is estimated at $1.2-2 trillion and the impact specifically on the transport and logistics sector is predicted to be $400-500 billion, equating to 4.9-6.4% of the market.



AI is being used to analyze sales data in order to more accurately predict demand for goods and thus creating efficiencies. In this application “[t]he sales forecast model is progressively upgraded by using an AI to perform learning on the difference between predicted and actual sales”, as well as determining which model is appropriate on a product-by-product basis. As well as sales data, AI can analyze “online browsing data, YouTube views, and social media conversations” in order to forecast any peaks or drops in demand for a product, as well as predict the next big trend. A software solution from ToolGroup draws on machine-learning to optimize supply chain of new product launches, with an “algorithm [which] learns from early sell-in and sell-out demand signals...layers this output to determine more accurate demand behavior, [and] feeds through to optimized inventory levels and replenishment plans.”
Companies that are using AI in this application include Hitachi, who are applying AI “for analyzing these huge amounts of data” and “building a model...that could not be handled manually”. The food manufacturer Danone uses “machine learning capabilities to analyze their demand planning” and have already seen significant benefits, with 20% lower margin of error in their sales forecast and a drop of 30% in lost sales." Unsurprisingly, e-commerce giant Amazon also applies AI to help model demand. Their director of machine learning explained that the company “has algorithms to predict demand for hundreds of millions of products it sells, often as much as 18 months ahead”.


Efficiencies can be gained before goods leave the warehouse, with AI analysis of “real-time data from both automated materials handling systems and smart-equipment”. This can provide route optimization for “forklifts handling inbound and outbound cargo”, which both cuts fuel costs and enhances worker safety. In 2016 Hitachi developed an AI tool “to understand worksite improvements and environmental changes”, and instruct accordingly. Its two-month demonstration test “confirmed the effectiveness of this system for improving distribution warehouse work”, resulting in a work reduction of 8%".


AI can be used to predict when mechanical failures are likely to occur, and so when is the optimum time for preventative maintenance. As mechanical failures “are one of the most expensive problems shipping companies currently face”, this is another aspect where AI, in conjunction with IoT sensors, can optimize the transport and logistics process. Machine learning algorithms are able to “learn” “which statistical indicators most accurately predict when a vehicle will be in need of repair”. Currently, the US air force and defense department are in the early stages of applying this sort of technology “to scan maintenance logs and past technical problems for signs that aircraft are wearing out”.


Route optimization powered by AI ensures that transport and logistics costs are minimized, by taking into consideration all the factors that could delay a delivery. AI “can optimize routing of delivery traffic, thereby improving fuel efficiency and reducing delivery times” as well as "leverage historical trip sheets and real-time statistics to accurately predict estimated delivery time. This has been demonstrated by the 15% fuel cost savings reported by an unnamed “European trucking company”. DHL uses machine learning to analyze 58 data parameters in order to predict delays in air freight deliveries “up to a week in advance”.
Machine-learning tools from TransVoyant and IBM also analyze data to forecast any issues with transport and logistics. The tool from IBM, provides shipping companies with analysis of the effect “severe weather will have on their operations”. The tool from TransVoyant goes even further, analyzing up to “one trillion events each day from sensors, satellites, radar, video cameras and smartphones” in order to assess the effect of “weather conditions, port congestion and natural disasters”.
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Mezcal Market

The Mezcal market is experiencing rapid growth within the U.S. and globally. The US market size for Mezcal is $126 million, up from $10 million in 2005. Experts forecast that it will continue to grow vigorously and North America will be the largest market for Mezcal.

Since Mezcal is produced in Mexico and imported to the United States, most data found is based on the global market. We were, however, able to find a source that mentioned the market size of Mezcal in the US but nothing more was found/mentioned about the US market. As such, we decided to take a more global approach to make up for the lack of information found for the US.


Most Mezcals are made in small batches by farmers using techniques that have been passed down for centuries, which contributes to its growing popularity and appeal. Produced in nine states in Mexico, the drink is typically consumed straight in Mexico and the U.S. Key vendors include Destilera Tlacolula, Ilegal Mezcal, Pernod Ricard, Pierde Almas, and William Grant & Sons.

The global Mezcal market is expected to expand at a compound annual growth rate of 17.8% from 2017-2022. The demand for Mezcal with 100% Tequila concentrate will increase through 2022. Higher concentration of Tequila is preferred for keeping the drink additive-free, and would also be more cost-effective since 100% agave Tequila is likely to cost more than a bottle of Mezcal with 100% concentration of Tequila. By the end of 2022, it is expected that over $840 million worth of Mezcal will be consumed worldwide.


In 2017, more than 80% of revenues procured in the global Mezcal market will be from sales of Mezcal Joven. Through 2022, Mezcal Anejo will be the fastest-selling product in the global market. Due to its proximity to Mexico, North America will be the largest market for Mezcal. Latin America will be the second largest, expected to procure $150 million value by the end of 2022. The European market is anticipated to reach a similar value by 2022.

Through 2022, Mezcal will be predominantly sold in hotels, restaurants and cafés, but specialty stores will see the highest growth rate. In 2017, specialty stores are anticipated to account for more than one-fifth of the global Mezcal market size. And, towards the end of 2022, the sales of Mezcal registered by specialty stores around the world are forecasted to reflect the fastest CAGR of 19 percent. Online retailers and modern trade outlets are also likely to increase in value, up to $40 million between 2017 and 2022.


Overall, the U.S. and global market for Mezcal is anticipated to experience significant growth through 2022, with North America being the largest market for Mezcal.
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Startup Studio Names

The concept of a startup studio is relatively new and therefore, there is not yet a consistent term used to describe them. Our research found 16 alternative names or terms for "startup studio." Each of these terms was either used by a company identified as a startup studio in the company description or was used as a synonym in an article on startup studios or one of the established alternate terms.

Alternative names

1. Venture studio
This term was used by Design for Revolution (DFR) and Midealab to describe their companies. Both companies are included in an article listing startup studios.

2. Venture builder
This term was used by RockaLabs and BTwinz Ventures to describe their companies. Both companies are included in an article listing startup studios.

3. Company builder
This term was used by Polymath Ventures and also Up to Eleven to describe their companies. Both companies are included in an article listing startup studios.

4. Tech startup ecosystem builder
This term was used by Livit to describe the company. Livit is included in an article listing startup studios.

5. Startup factory
This term was used by INNVATION to describe the company. INNOVATION included in an article listing startup studios.

6. Entrepreneurial ecosystem creator
This term was used by Co.Builders to describe the company. Co.Builders is included in an article listing startup studios.
7. Factory of startups
This term used by Startup Maker to describe the company. Startup Maker is included in an article listing startup studios.

8. Innovation lab
This term was used by Liquid Labs to describe the company. Liquid Labs is included in an article listing startup studios.
9. Venture creation/creator
This term was used by FoundersLink to describe the company. FoundersLink included in an article listing startup studios.
10. Startup builder
This term was used by Itnig to describe the company. Itnig is included in an article listing startup studios.
11. Digital product studio
This term was used by NEVERBLAND to describe the company. NEVERBLAND is included in an article listing startup studios.
12. Technology startup creator/launcher
This term was used by Pioneer Square Labs to describe the company. Pioneer Square Labs is included in an article listing startup studios.

13. Venture developer
This term was used by 212Media to describe the company. 212Media is included in an article listing startup studios.
14. Technology studio
This term was used by Zuma Ventures to describe the company. Zuma Ventures is included in an article listing startup studios.

15. Production studio
This alternative term was found in an article listing venture studios. "Venture studio" has already been identified as an alternative term for startup studio.

16. Startup foundry
This alternative term was found in an article listing venture studios. "Venture studio" has already been identified as an alternative term for startup studio.


In conclusion, there are many terms used to describe startup studios. We were able identify 16 different terms in our research.

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Active Shooter Technologies

Our research found multiple technology-based approaches schools are using to prevent and respond to active shooter situations in schools. Technologies found include virtual training, digital panic buttons, shot-detection technology, automatically locking doors and live video feeds. In many instances, schools are combining these technologies to create a comprehensive system.

Virtual Training

Virtual training, which uses virtual reality technology to run participants through active shooter scenarios, is being adapted for use by schools. The training is intended to augment live training drills, not to replace it. For example, the Department of Homeland security updated its Enhanced Dynamic Geo-Social Environment (EDGE) Virtual Training to include a simulation of an active shooter incident in a school. The school depicted in the training includes a variety of areas that many schools have, including many classrooms, a cafeteria, an auditorium and a gymnasium. Trainees collaborate with one another in the training, which helps improve their coordination and communication.

Digital Panic Buttons

There are multiple apps available that offer digital panic buttons for school staff. One example is PikMyKid, which was initially designed to assist schools in organizing the after school pick-up process, but was later updated to include digital panic button technology. The basic idea of a digital panic button is that any school staff member who identifies a school shooter or other threat presses a button in the app, which triggers an alert that is sent to emergency officials. The device’s microphone is also activated, which then sends a continuous audio signal to emergency responders. Developers of PikMyKid have also worked with FacilityONE, a company that makes digital blueprints, which are then loaded into the safety profile associated with the school and are made available to emergency responders in case of an active shooter situation or other emergency.

Shot-Detection Technologies

Shot-detection technology was previously used by the military to detect missiles and snipers as well as in New York City, Chicago, and Baltimore to identify the location of gunshots within the city; however, schools are beginning to install this technology to be used in the case of an active shooter. Schools that use this technology have had sensors installed throughout the school. The sensors are capable of distinguishing gunshots from other similar sounds, like firecrackers, and triangulating the sound to provide an accurate location of gunfire within the school. The information is then relayed to emergency responders and administrators if shots are fired within the school. Sensor can also be linked to other systems within the school to further enhance response. For example, the sensors can be linked to video surveillance systems to redirect cameras to the source of the gunshot or to automatic door locks to prevent movement of the shooter throughout the building.

Automatically Locking Doors and movement tracking

A company called Virtual Command has developed a system that locks all doors within the school as soon as a teacher sounds an alarm that an active shooter or other threat is present. The doors are built of reinforced steel and bullet proof glass to prevent the shooter from gaining access. Police can then take control of the school using a computer terminal and can track the whereabouts of the shooter using video surveillance and motion detectors. The system can also be configured to allow police to track the shooter's movements through the building using motion sensors and even encourage the movement of the shooter in a specific direction using smoke released from the ceiling, making apprehension easier. The company plans to add the ability for police to use the PA system to communicate with the shooter for negotiations to future versions.

Live Video Feeds

Many schools have video monitoring systems. Allowing law enforcement access to these feeds is strategy schools are using to respond to active shooter situations. With access to these video feeds, emergency responders can identify the safest entry point as well as the location of victims needing medical care. For example, schools in the Detroit area are allowing Macomb County’s Communications and Technology Center (COMTEC) direct access to video feeds in public areas within local schools. This includes feeds such as hallways, classrooms and libraries as well as outside areas, such as parking lots.

Combining Approaches

Many schools who are using technology to prevent and respond to school shootings are using more than approach. Most articles found talked about several of these approaches and noted that they are used in combination. For example, one system combines gunshot detection, video surveillance and automatically locking doors.

Historical Approaches

In order to identify what procedures and products have historically been used in response to school shootings, we identified approaches school used to school shooting after school shootings that occurred more than 2 years ago. Therefore, the sources in this section are older than the typical 2 years included in Wonder research. The most prominent school shootings mentioned in the media and other sources in terms of changes to school security and procedure are Columbine (1999) and Sandy Hook (2012). Therefore, strategies that were employed during and after these incidents were the focused on for the historical perspective.

After the Columbine shooting, schools employed many strategies to try to improve security and safety. Many schools installed metal detectors and hired police officers to patrol campuses. They also changed procedures around student identification, such as requiring students to carry IDs and around what students could bring to school, such as banning backpacks or requiring clear backpacks. Schools also began training staff and students to identify and report threats.

After the Sandy Hook shooting, schools installed security cameras that would record the arrival and departure of every staff, student and visitor. They also installed technology that controlled entry into the school, requiring school staff to buzz each visitor into the building after determining their reason for being there. Schools again increased law enforcement presence and held active shooter and lock down drills. Many of the strategies implemented after Columbine and Sandy Hook continue to be utilized today.


Technological solutions are being utilized in a variety of ways to prevent and respond to active shooter situations in schools. Such solutions are targeted at alerting law enforcement quickly, preventing additional loss of life and providing enhanced information to responders.