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Ready for Restaurant Robots? They May Be the Answer




One industry really struggling during the pandemic is restaurants. Many were shut down, only allowed to serve takeout with the need to socially distance. Restaurant workers have been forced to get other jobs to make ends meet, leaving a staffing shortage. One restaurant owner thinks she has the answer to her staffing problems: restaurant robots.

Restaurant Robots at Your Service

Restaurant owners were left with very few options. If they remained closed, they faced going out of business. If they defied government orders and remained open, they faced hefty fines. Complicating this, the staff hasn’t always stuck by them. They’ve either found other restaurants that were open or left the industry altogether.

Joy Wang, the owner of Mr. Q Crab House in Hollywood, Florida, found an answer. She’s been using restaurant robots to fill out her staff.

Restaurant Robots Peanut

Wang tried to fill the positions with humans, specifically for the busy weekend shifts. She said her former staff “would rather sit at home and collect unemployment.”

She put three robots in her restaurant at a price of $10,000 each. She won’t need to worry about them catching COVID-19 or passing it off to patrons. They don’t earn tips, and they won’t leave to work for a competitor. They can even sing Happy Birthday for special occasions.

One of the robots has been named “Peanut,” while the other two are unnamed. The four-foot Peanut will greet you and take you to your table. The other two bring your food to the table and also clear the dishes when you’re done. They can carry more plates of food than humans.

Restaurant Robots Delivering

The restaurant robots don’t take orders or respond to commands. Human servers still take orders and accept payments. Like humans, the robots do need to take breaks. When their batteries are low, they will announce that they are leaving but will be back.

The Path Forward

The restaurant robots are not alone. Dominos recently announced it was beginning to have robots deliver orders in Houston, Texas. There are also food stores making deliveries possible via robots.

Some of the customer service robot technology was in the works before the pandemic, so it can be assumed that the robots are here to stay, even after we finally close the door on the global health crisis. It brings up the question of how far it will go and how many more industries will accept their help.

Read on to learn about a new Boston Dynamics robot, Stretch.

Image Credit: Sun Sentinel and South Florida Sun Sentinel Twitter

Laura Tucker Laura Tucker

Laura hails from the Chicago area and has been a writer and editor covering news, entertainment, and technology for nearly 20 years and has been with Onlinetivity since its inception, editing and covering news. In her spare time, she enjoys exploring new devices and mobile apps.

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Cyber Security

Shifting Threats in a Changed World: Edge, IoT and Vaccine Fraud




The administrator of your personal data will be Threatpost, Inc., 500 Unicorn Park, Woburn, MA 01801. Detailed information on the processing of personal data can be found in the privacy policy. In addition, you will find them in the message confirming the subscription to the newsletter.

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IoT Managed Services: Simplifying the Hidden Complexities of IoT




Managed Services
Illustration: © IoT For All

IoT solutions are shifting from a convenience to a business necessity for many industries. As IoT adoption grows, companies are tasked with figuring out how they will deploy complex technology solutions. When assessing how to implement IoT solutions, businesses can choose to do nothing, do it themselves, patch together a solution from multiple vendors, or engage with an IoT managed services provider.

study by James Brehm and Associates found that 49% of respondents stated that enterprises don’t have the proper staff in place to design, implement, and maintain IoT solutions. That makes sense, especially considering that nearly three-quarters of IoT projects fail to make it past proof-of-concept. The reason many IoT initiatives fail is because of the hidden complexities of deploying connected devices.

Because businesses tend to be focused on IoT applications and the end-user experience, many of the challenges in deploying IoT solutions tend to catch them by surprise. Too often, they find out after attempting to deploy new solutions with in-house resources that they lack the expertise and experience to launch IoT initiatives in an efficient, cost-effective way.

Lack of expertise and resources is one of the most common obstacles to a successful IoT deployment, along with interoperability and compatibility, compliance, security risks, solution deployment, data actionability, and ecosystem diversity. Businesses most often find success with their IoT initiatives by partnering with IoT managed services providers.

IoT managed services providers handle the complexities of IoT with a broad range of services and expertise to streamline the process of procuring, connecting, configuring, and deploying devices across the globe.

Engaging with an IoT managed services provider enables businesses to manage risks, reduce costs, and improve time to market. They accomplish this through comprehensive device management, wireless connectivity, network management, and forward and reverse logistics.

When it comes to selecting a managed services partner, it’s critical to work with an expert in IoT that supports the complete device lifecycle, from solution design to end-of-life. This end-to-end solution for IoT-managed services allows businesses to focus on their core business and customer experience.

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Artificial Intelligence

Powering the Next Wave of Healthcare Innovation with AI




AI Healthcare
Illustration: © IoT For All

There’s no doubt that data is poised to transform healthcare like it has so many other sectors, but it’ll need a helping hand. Today, healthcare providers collect exabytes of patient data from hospitals, clinics, imaging and pathology labs, and more. This data contains a wealth of insight into human health, but its lack of structure and sheer volume means it’s well beyond the limits of human ability to decipher it.

Fortunately, sophisticated AI and machine learning solutions can carry the torch of innovation.

In healthcare, the value of machine learning is its capacity for processing massive data sets that are far beyond the scope of human ability. Raw, unstructured data goes in, and clinical insights come out, helping physicians plan and provide better care at a lower cost. While the sky is the limit as far as the benefits of machine learning, constructing these complex algorithms takes time. In the next five to 10 years, we expect to see medical professionals reaping the dividends of healthcare-based innovation in these areas:

Advanced Image Analysis

Medical professionals are highly trained, and some of their work reflects their tremendous value add. However, there’s still a need for professionals to spend time on repetitive tasks such as image analysis. In radiology, for example, doctors spend time looking at images from CT scans, MRIs, ultrasounds, PET scans, mammography, and more. AI-assisted imaging solutions use the technology’s advanced pattern-recognition capabilities to highlight image features, identify early predictors of cancer, prioritize cases, and cut down on the volume of labor required to perform accurate diagnoses. As AI processes more and more data sets, the technology will inevitably eclipse the ability of human doctors to spot the signs of disease as early as possible.

Disease Detection

Due to its high cost, healthcare imaging generally takes place only to confirm a diagnosis. It’s an effective solution, but one that AI promises to upend and replace. By conducting an in-depth analysis of huge amounts of historical data, AI can predict the possibility of sickness or disease at incredibly early stages. For example, by looking at an entire patient population that closely matches the demographic of a specific individual in addition to the medical history of relatives, AI could conclude that a patient is very likely to develop a malady such as heart disease years before a doctor could ever accurately make a diagnosis.

Drug Discovery

We’ve all seen firsthand how important it is to design and produce effective drugs and vaccines to combat a newly discovered disease. Historically, this process has taken massive investments of time and money, with development timelines extending out to more than a decade in some cases. The ability of AI to cross-reference drugs that are known to be safe and effective and replicate parts of their formulas to suggest new iterations could be groundbreaking, potentially saving countless lives and helping to prevent the next global pandemic.

Digital Consultation

The pandemic undoubtedly spurred innovation in the telehealth space. However, there’s still a long way to go to make virtual visits as effective as a physical visit to the doctor’s office. AI can help close that gap in numerous ways. Machine learning and natural language processing (NLP), for example, will help facilitate symptom collection using just a patient’s voice. Combined with an analysis of the patient’s electronic health record, AI can highlight probable health concerns for doctors to review. By processing information ahead of time, AI increases the volume of patients that doctors can handle, improves the efficacy of virtual visits, and even minimizes the risk of infection from physical interactions as a result.

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Big Data

IoT vs. Serverless Computing




The Internet of Things (IoT)
describes an interconnected network of physical and digital devices, sensors,
mechanical components, and communication protocols with the ability to transfer
and exchange data machine-to-machine or machine-to-interactions.

The serverless computing model is cloud-based and all its resources are managed by the service provider. The client is charged based on the consumption of particular applications. Serverless is widely offered as Infrastructure as a Service (IaaS).

Cloud and serverless are ideally suited for each other because the methodology for managing resources in each is very similar. The Google Cloud Platform is an example of how resources are managed on a typical serverless setup. The traditional cloud service providers offering IoT platforms are increasingly moving toward the serverless model to provision low-cost and maintenance-free IoT services.

What Do IoT and Serverless Computing Have in Common?

are some similarities between these two emerging technologies:

  • Both IoT and serverless have introduced innovative ways of managing networks of connected devices
  • Both have received immense response from business operators and developers
  • They are still maturing in terms of system integration models
  • They have shown promise in terms of future interoperability. IoT implementations on the serverless will push vendors to invest in cross-platform portability to capture a wider market share

According to What Serverless and the Internet of Things Can Learn from Each Other, the IoT technology culture is headed toward serverless, and the recent buzz at conferences is the successful mingling of IoT and serverless. The general pulse of the market is that IoT implementations will drive portability across serverless platforms.

Another term heard in this market is “architecture map.” As IoT implementations on the serverless continue to mature, architecture maps will play a significant role in developing the designs of such networks and pushing serverless vendors to portability for higher industry use cases.

Serverless as an Emerging Platform for IoT Innovation

Whether it is Amazon’s EC2 or AWS Serverless, the shifting of the central server to the cloud has transformed daily business activities. Business operators are getting used to a third-party service provider provisioning and managing all their business data operations. The adoption of serverless across businesses will remove the necessity for heavy investments in in-house infrastructure and technical staff. site has more about this innovative “outsourced data center.”

In a way, the serverless computing model has propelled the rise of IoT implementations because the availability of low-cost but premium IoT platforms—with their integration and management services—have made it easy for cost-conscious business operators to take advantage of these innovative technologies with minimal headaches and operating expenses.

The serverless computing model (rather than open-source or custom) is seen as a primary driver of ready-made IoT platforms of the future, as described in the article Should You Use Serverless Architecture for Your IoT Solution?

Serverless promotes fast IoT adoption with no investments in infrastructure, technology, or personnel—with the promise of vast returns. A Medium article proposes PaaS, an SaaS combined serverless model, whose USPs are zero maintenance and minimal operating cost. Serverless Computing and Serverless Architecture: An Overview of BaaS, FaaS, and PaaS has more about these cloud services.

The article highlights the following benefits of serverless:

  • Provides an easy method to
    convert capital expenditure into an operating budget
  • Does not require any
    in-house systems administration
  • Significantly reduces
    development and deployment timeframes expenses, thus reducing time-to-market
  • Scalable by design

Why IoT and Serverless Fit So Well! brings up some technical points like the serverless being naturally suitable for on-demand processing, scalable computing power, and ready infrastructure for development work.

The Developing Countries: The Level-Playing Field for Serverless, Cloud,
and IoT

exposed to advanced telecommunication technologies after decades of “standby”
status, developing countries are hungry to explore all these technologies for
the fullest advantages to domestic business communities. In the coming years,
you may see Amazon, Microsoft, and Google engaged in a battle to capture these
new markets for cloud IoT services.

Serverless, cloud, and IoT will find rich markets in the developing world, which will want cost-competitive measures to upgrade their business models in a growing global business world. It is easy to understand why globally competing businesses will jump to invest in serverless; interesting use cases are discussed in Serverless Computing Use Cases.

Top Roles of Cloud Computing in IoT describe how IoT and the cloud play the roles of “data pipelines” and data storage” respectively in an interconnected business landscape. Together, these two technologies seem to be beckoning the serverless model to take over as the final facilitator of IaaS, FaaS, and PaaS.

IoT vs. Serverless: Some Unexplored Concerns

When so much positive energy is revolving
around the concept of IoT implementation on a serverless computing environment,
is there any hidden dark spot to worry about? Well, there is. The serverless
environment, like the cloud, has some unexplored issues of data security, data
leakage, and data loss.

The primary reason why technology vendors and service providers should invest in more research before deploying “IoT on Serverless” on a commercial scale is the uncomfortable question surrounding Data Governance. This is not a new concern—it has been a longstanding issue ever since businesses were offered outsourced data services.

While IoT on private or hybrid cloud platforms has been accepted, how the global business community, especially the developing countries, will perceive IoT on serverless is still to be seen. Additionally, regulatory compliances may make things difficult for serverless vendors in the coming years.

The current pricing patterns of IoT services may also pose a problem for serverless environment in future. Execution-based pricing models in a serverless environment have pros and cons.

Image used under license from

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