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Linux Foundation, LF Networking, and LF Edge Announce Keynote Speakers for Open Networking & Edge Summit North America 2020

By Announcement

 

  • Industry’s Premier Open Networking & Edge Conference Features Keynote Speakers from AT&T, CNCF, Deutsche Telekom AG, Edgeworx, Equinix, Ericsson, Google, Huawei, IBM, Rakuten Mobile and more 
  • The full conference schedule will be announced on March 5th featuring business, technical and architectural sessions

 

SAN FRANCISCO, February 20, 2020The Linux Foundation, the nonprofit organization enabling mass innovation through open source, along with co-hosts LF Networking, the umbrella organization fostering collaboration and innovation across the entire open networking stack, and LF Edge, the umbrella organization building an open source framework for the edge, today announced initial keynote speakers for Open Networking & Edge Summit (ONES) North America 2020. The event takes place April 20-21 in Los Angeles, California. 

Open Networking & Edge Summit (formerly Open Networking Summit) is the industry’s premier open networking event now expanded to comprehensively cover Edge Computing, Edge Cloud and  IoT. The event enables collaborative development and innovation across enterprises, service providers/telcos and cloud providers to shape the future of networking and edge computing with a deep focus on technical, architectural and business discussions in the areas of Open Networking & AI/ML-enabled use cases for 5G, IoT, Edge and Enterprise deployment, as well as targeted discussions on Edge/IoT frameworks and blueprints across Manufacturing, Retail, Oil and Gas, Transportation and Telco Edge cloud, among other key areas.

Keynote speakers this year include:

  • Andre Fuetsch, Executive Vice President & Chief Technology Officer, AT&T Services, Inc.
  • Dan Kohn, Executive Director, Cloud Native Computing Foundation
  • Alex Choi, Senior Vice President of Strategy and Technology Innovation, Deutsche Telekom AG
  • Farah Papaioannou, Co-Founder and President, Edgeworx, Inc.
  • Anders Rosengren, Head of Architecture & Technology, Ericsson
  • Justin Dustzadeh, Chief Technology Officer, Equinix
  • Aparna Sinha, Director of Product Management, Google Cloud
  • Bill Ren, Chief Open Source Liaison Officer, ICT Infrastructure Open Source GM, Huawei
  • Marisa S. Viveros, Vice President of Strategy and Offerings, IBM
  • Ashiq Khan, Head of Cloud and NFV, Rakuten Mobile, Inc.
  • Arpit Joshipura, General Manager, Networking, Edge & IoT, The Linux Foundation
  • Heather Kirksey, Vice President, Community and Ecosystem Development, The Linux Foundation

Additional keynote speakers, as well as the full schedule of sessions, will be announced the first week of March.

Conference Registration is $950 through March 10, 2020 with additional registration options available including $300 Hall Passes, $600 Academic Passes, and $500 Student Passes.  Non-profit and group discounts are available as well; details are available on the event registration page. Members of The Linux Foundation and Linux Foundation Projects (including LFN and LF Edge) receive a 20 percent discount on all registration fees; contact events@linuxfoundation.org to request a member discount code. Applications for diversity and needs-based scholarships are currently being accepted; for information on eligibility and how to apply, please click here.

Open Networking and Edge Summit North America 2020 is made possible thanks to Platinum Sponsors Cloud Native Computing Foundation, Ericsson, and Huawei, Gold Sponsor IBM, and Silver Sponsor Red Hat. For information on becoming an event sponsor, click here.  

Members of the press who would like to request a press pass to attend should contact Jill Lovato at jlovato@linuxfoundation.org.

Additional Resources 

About The Linux Foundation
The Linux Foundation is the organization of choice for the world’s top developers and companies to build ecosystems that accelerate open technology development and industry adoption. Together with the worldwide open source community, it is solving the hardest technology problems by creating the largest shared technology investment in history. Founded in 2000, The Linux Foundation today provides tools, training and events to scale any open source project, which together deliver an economic impact not achievable by any one company. More information can be found at www.linuxfoundation.org.

The Linux Foundation Events are where the world’s leading technologists meet, collaborate, learn and network in order to advance innovations that support the world’s largest shared technologies.

The Linux Foundation has registered trademarks and uses trademarks. For a list of trademarks of The Linux Foundation, please see our trademark usage page: https://www.linuxfoundation.org/trademark-usage.

Linux is a registered trademark of Linus Torvalds.

 

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Akraino Edge Stack Use Cases: Baidu’s End User Story

By Akraino Edge Stack, Blog

Written by Baidu representatives who actively participate in Akraino’s TSC

Edge scenarios are very important commercial scenarios for AI applications. There are many type of hardware, OSes, etc. It is hard for AI application providers to adapt their products to all these edge components. Fortunately, the Akraino community and LF Edge member companies can help to do the validation/development or to support their products. The AI application providers need to state their requirements or cooperate with member companies in their Blueprint validation/integration labs. In this way, the AI application providers  are more likely to find potential partners and potential commercial market.

The AI Edge Blueprint Family

LF Edge member Baidu has deployed School/Education Video Security Monitoring blueprint. With this blueprint, teachers and school authorities could conduct a full evaluation of the overall class and the concentration of individual students, helping to fully understand the real time teaching situation. According to the concentration data of each course, teachers and school authorities can conduct knowledge test and strengthen. And the School/Education Video Security Monitoring blueprint has been deployed in Beijing, Shanghai, Hangzhou(Zhejiang Province), and many other cities in China.

The AI Edge Blueprint mainly focuses on establishing an open source MEC platform combined with AI capacities at the Edge, which could be used for safety, security, and surveillance sectors. Currently it has been highly supported by partners like Arm and Intel. And both Arm and Intel infrastructures, such as Servers and GPU cards,  have been implemented in respective scenarios.

A picture of the architecture

The AI Edge: RoboTaxi blueprint proposal has been deployed in Changsha, Hunan province, China. Commercial code is being run. The community version of code will be available in Q1 of 2020.

For more information about the Akraino blueprints or end user case stories, please visit the wiki: https://wiki.akraino.org.

NRF 2020 Intel Demo: Real Time Sensor Fusion for Intelligent Loss Prevention

By Blog, EdgeX Foundry

Written by Kristen Call and Camilo Dennis, Intel Open Retail Initiative, LF Edge members and EdgeX Foundry contributors  

ORI: Technology Collaboration to drive innovation in Retail

Intel announced the Open Retail Initiative (ORI) last year at the National Retail Federation tradeshow.  ORI is a collaborative effort led by LF Edge member Intel and top technology companies who believe that open, accessible solutions will accelerate iteration, flexibility, and innovation at scale.   To empower digital transformation in retail, ORI promotes EdgeX Foundry as a common, open framework to allow retailers to access data across applications, removing silos and unlocking insights that improve services and experiences.  To learn more about ORI visit http://bit.ly/Intel-OpenRetail.

For the one-year anniversary of ORI, six initiative members Edgify, Flooid, Shekel and LF Edge members HP, IOTech and Intel inspired by the initiative, worked together on a demo for the Intel booth that showcased the value of Real Time Sensor Fusion for a loss prevention use case at self-checkout. The retail environment has become incredibly complex. The latest technologies enable data-driven experiences and unlock business value like never before, yet there is still a lack of interoperability making it difficult for retailers to deploy integrated solutions with speed and ease.  The demo illustrates how integration roadblocks can be a thing of the past.

The demo pulls together real time data through the EdgeX middleware from different common systems including POS real-time transaction log, CV-based object detection, scale solution, and RFID, and data fusion—all in a single pane of glass.

NRF 2020:  Intelligent Loss Prevention – A collaboration of six partners, inspired by the spirit of Intel’s Open Retail Initiative (ORI), the demo showcased Real Time Sensor Fusion (RTSF) using EdgeX open source middleware to combine POS, RFID, Scale and Computer Vision data —all in a single pane of glass.

Liberate your data using EdgeX Foundry

Much of the data created in physical retail today, i.e. at brick and mortar, is not used or a portion of it is aggregated to be used later.  Data is usually trapped in silos and make it difficult for retailers and technology integrators to merge and use data, especially in real time.  Innovation is hampered because of:

  • Environmental complexity due to lack of interoperability
  • Deployment of data-driven experiences in brick and mortar is limited or not possible with traditional architecture
  • Lack of unified standards impeding digital transformation efforts

Intelligent Loss prevention is just the beginning, Intel and its partners used this demo to demonstrate what’s possible when a community works together and uses open standards to solve today’s real retail problems:  LF Edge’s EdgeX Foundry architecture allows access to data across applications in real time allowing retailers and technology vendors to unlock insights that improve services and experiences.  All this is possible by augmenting common existing assets, rather than rip and replace.

Using real time sensor fusion to solve a retail problem-Proof of Concept

Retailers increasing self-checkout for customer convenience continue to face challenges to detect and prevent theft.  No single sensor, i.e. RFID or scale, is theft proof at self- checkout.   That said, combining different sensors, each with unique detection attributes can improve object detection and reconciliation accuracy.  The tradeoff though, in traditional architecture, is a complex integration effort among sensors and the Point of Sale solution. Using a modern architecture, a community approach and open standards integration complexity becomes a thing of the past.

The POC combined data from RFID, Scale, and CV POS  RTTL to determine if an item had been scanned or not.  RFID was Intel based open solutions RSP.   The discrepancy was displayed differently showcasing how the data could be reutilized based on the end users preferences without a large effort.  For detail information on the reference design used for sensor fusion for loss detection at self-checkout, including use of machine learning to connect point-of-sale systems, weight scale sensors, cameras, and RFIDs to accurately detect checkout items visit https://software.intel.com/en-us/iot/reference-implementations/point-of-sale-loss-prevention

Reduce development and integration time to focus on value add

Back to the caveat of having to integrate with a point of sale solution for the loss prevention use case and the challenges mentioned earlier from to lack of interoperability and data silos and how to tackle them.  After the POC described above, Intel, fellow ORI members and the EdgeX community collaborated to create an NRF demo using enterprise ready applications.

According to flooid (formerly PCMS) a traditional integration with a POS solution can take 6 months vs. the weeks the demo team had to work on this demo which was only possible by:

  • Use of data and protocol standards and EdgeX middleware
  • The EdgeX based architecture allowed partners to focus on their own application and contribution to the use case and not on integration
  • Reusable components from EdgeX community.  i.e. the weight scale device service
  • Minimal impact to the participating applications, but its noteworthy to say the complexity of managing each application did not change

The entire demo took 3 months.  The speed of integration took 2 hours to 2 weeks for each vendor. Flooid was able to integrate with EdgeX in a couple of hours.  It took a couple of weeks for all the other applications to integrate to EdgeX and a 5-day onsite meetup to bring all together.   The remaining 2 months were dedicated to hardening the solution and for each vendor to work on nuances for the physical sensor and to tune their specific applicational requirements.  Finally, each application provider focused on their area of expertise, i.e. POS did not have to be a CV or RFID expert and vice versa.  As a result a System Integrator and or the POS provider can focus on new use cases to build business value while reducing the integration effort and risk.

Architecture provided by IOTech

Call to Action

Commit to the initiative and join ORI, let us know if you have a use case that you’d like to work together on.  Collaborate on the EdgeX Vertical Solutions Working GroupContribute to the EdgeX Foundry project or influence standards by becoming a LF Edge member and share implementation stories such as these.

For more about EdgeX Foundry’s Journey in retail, check out this video:

 

State of the Edge 2020: Democratizing Edge Computing Research

By Blog, Open Glossary of Edge Computing, State of the Edge

Written by Matt Trifiro, Open Glossary of Edge Computing TSC Chair, Co-Chair at State of the Edge and CMO at Vapor IO

State of the Edge 2020, a vendor-neutral report supported by The Linux Foundation’s LF Edge contains unique and in-depth research on edge computing, covering the major trends, drivers and impacts of the technology. The report provides authoritative market forecasting and trend analysis from independent contributors, bringing authoritative research on edge computing to everyone.

Edge Computing and LF Edge

Many believe edge computing will be one of the most transformative technologies of the next decade, and that by positioning dense compute, storage and network resources at the edge of the network new classes of applications and services will be enabled which support use cases from life safety to entertainment.

The Linux Foundation’s LF Edge has greatly contributed to the growth of edge computing in the industry, both in terms of technical projects and a deep shared understanding of the concepts and terminology underpinning this new area of technology.

 

One of the key projects within LF Edge is the Open Glossary of Edge Computing. This project seeks to harmonize the terminology used across the industry when discussing edge computing and has been adopted by a number of projects and contributors in the community. These community members recognize that without a common and accurate definition of key terms and concepts, it is much harder to collaborate on challenges.

State of the Edge

The Open Glossary of Edge Computing was originally born as part of the inaugural State of the Edge report in 2018, where an initial version was published and included as part of the report. Shortly after this, the Open Glossary of Edge Computing was adopted as an LF Edge project.

State of the Edge is itself an open and collaborative community of organizations and individuals who are passionate about the future of edge computing. The project looks to advance edge computing within the industry through consensus building, ecosystem development and effective communication. To that end, State of the Edge reports are written and published using contributions from a diverse community of writers and analysts. By including many voices, State of the Edge publications avoid the often incomplete, skewed and overly vendor-driven material and research typically available.

Multiple reports have been published to date, and more are planned for release during 2020, including coverage of topics highly relevant to edge computing, such as 5G networks. In addition, the State of the Edge 2020 report contains the latest version of the Open Glossary of Edge Computing, which reached version 2.0 during 2019.

 

Democratizing Edge Computing Research

The first State of the Edge report in 2018 focused on establishing a baseline of knowledge from across the edge computing industry. This made it possible for readers to accurately assess what edge computing meant for them, their customers and their unique use cases. This first report covered what were many new and often misunderstood concepts, tying them together in a way that enabled more people than ever before to appreciate and understand the edge.

When it came to the State of the Edge 2020 report, following extensive feedback and surveys, the collaborative team decided that market forecasting on edge computing was hard to come by, and in high demand. Though forecast models on edge computing exist, they are often proprietary and are not built transparently. Moreover, they are typically locked behind expensive paywalls that limit the number of people that can benefit from them.

By drawing on the expertise of professional researchers and well-regarded contributors, State of the Edge has released its first market forecast, along with a comprehensive narrative that discusses the new trends in edge computing.

The State of the Edge is run like an open source project and publishes all of its reports under a Creative Commons license, making it freely available to anyone who is interested. This approach allows the community to benefit from shared knowledge and valuable research on edge computing, without limiting it to those with money to spend.

Available to Read Now 

The State of the Edge 2020 report is available to read now for free. We encourage anyone who is interested in edge computing to give it a read and to send any feedback to State of the Edge.

LF Edge Member Spotlight: Dianomic

By Blog, Fledge, Member Spotlight

The LF Edge community is comprised of a diverse set of member companies that represent the IoT, Enterprise, Cloud and Telco Edge. The Member Spotlight blog series highlights these members and how they are contributing to and leveraging open source edge solutions. Today, we sat down with Tom Arthur, CEO at Dianomic, and one of the creators of Fledge, to discuss the importance of a growing ecosystem, their Industrial IoT framework, the impact LF Edge has made and what the future holds for the company.

Can you tell us a little about your organization?

Our company name is Dianomic Systems.  It is derived from the Greek word dianomi meaning distribution.  As you may have guessed, edge computing is a challenging distributed computing problem.

The fragmentation and distribution of industrial data, networking, processing, security and storage makes managing it complicated.  Simplifying industrial IoT application and system development with a ubiquitous open source stack, standards, and community is our mission.

With our community, we created FogLAMP in 2018 then contributed all the code to the LF Edge’s Project Fledge to help address the industrial data problem.  Fledge is a stack of integrated microservices that operate from sensor to cloud (the edge).  These services connect any sensor or machine data, aggregate data, buffer data, transform data, filter data, execute AI/ML operations, alert, visualize and forward data to any cloud or on-prem destination.

 

Why is your organization adopting an open source approach?

 The LAMP stack is largely responsible for the success of web application development.   Almost every web, ecommerce and social network developer consumed it.  Dianomic believes a similar open source stack is required for Operational Technology (OT) to help drive Industrial 4.0 application development.   This is the Fledge community’s mission.

We already have several public use cases and many not yet public proving the open source approach works.

At Jacksonville Energy Authority (JEA), they deployed Fledge to monitor substation transformer’s oil pumps, oil temperature, cooling fans, ambient air temperature and hydrogen gas.  They are now also testing infrared cameras to monitor heat other heat sources in the substation and in their water business monitoring pumps and bearings.   Using Fledge’s PHP based plugin architecture they developed a KAFKA north connection to be their single pub-sub system for all their IIoT data requirements.   The goal is complete predictive and conditional monitoring of all non-SCADA systems.  This KAFKA north service was then contributed to the Fledge stack for the community and supported by Dianomic.   Fledge is then tightly integrated with both their OSIsoft PI systems (that monitors SCADA and DCS systems) and their Oracle ERP and maintenance systems.

At General Atomics (a General Dynamics spin-out), the maker of the U.S. Airforce’s Predator drone, Fledge is used to help monitor the manufacturing quality of the fuselage, wings and stabilizers.   These components are made of composites where heat and humidity are tightly controlled.   Fledge is used with industrial grade explosion proof sensors to “green light” a process once appropriate temp and humidity levels are achieved.  Once again, using the plugin architecture, GA was able to tightly integrate the data and events with systems monitoring the rest of the factory keeping track of everything in context of the entire aircraft being built.   These integrations are also part of the Fledge stack today. 

Why did you join LF Edge and what sort of impact do you think LF Edge has on the edge, networking, and IoT industries?

There is no better organization to help govern, build communities and market the benefits of a Linux based OT equivalent of the LAMP stack.

What do you see as the top benefits of being part of the LF Edge community?

Working hand-in-hand with the premier computing, data management and networking companies that share the same passion and vision for open source projects to fundamentally help industrial developers build better machines, plants, factories and businesses.

What sort of contributions has your team made to the community, ecosystem through LF Edge participation?

Dianomic, Google, OSIsoft, industrial system integrators and industrial companies have all contributed to Fledge.  The LF Edge’s project Fledge started when Dianomic contributed the entire FogLAMP stack in winter of 2019.    At that time, the code was in its 8th release and had been commercially deployed in energy, manufacturing and mining operations.  Today, Fledge has ~30,000 commits and averages ~5000 commits/month.

What do you think sets LF Edge apart from other industry alliances?

The Linux Foundation’s history of delivering commercial grade open source software combined with the list of LF Edge membership is simply the best.   Members are serious and passionate about quality open source software, building strong communities and the markets served.

How will LF Edge help your business?

Of course, open source code with Apache 2 licensing is a great start for most software development today.  In Fledge’s case, the code is in its eighth release and deployed in industrial use cases for over a year.   Industrial developers can have more features, faster time to market and higher quality as their starting point!

 

Additionally, contributing FogLAMP to the Fledge project under LF Edge governance adds extra assurance and insurance for the developer.   They can feel confident in their decision to use and contribute to Fledge knowing the LF is backing the project and they remain in control of their own destiny with no cloud or other vendor locks.

What advice would you give to someone considering joining LF Edge?

Open Source is new to manufacturers and manufacturing is new to the Linux Foundation. So, the Fledge community consists of manufacturers, industrial equipment suppliers, integrators, OT system suppliers and technology suppliers.    Join us – help us, help you accelerate Industrial 4.0 adoption. It’s going to be fun!

To learn more about Fledge, visit the project page here.

 

 

 

 

Akraino 5G MEC Hackathon: Winners, Insights and More

By Akraino Edge Stack, Blog

Written byy Suzy Gu, CMTI 5G ICSV; Tina Tsou, Arm; Nitish Nagesh, UCSD; Guoxi Wang, UCI; Jerry Lin, Columbia University; Kangxian Xie, UCSD; Alex Reznik, ETSI

A few months ago, more than 76 developers gathered to participate in the Akraino 5G MEC Hackathon, sponsored by LF Edge, China Mobile Technology, ETSI and ETSI MEC. Attendees participated in-person at the Qualcomm campus in San Diego, a breakout venue in Columbia University and virtually via Zoom conference.

Different blueprints and solutions will be worked through in real time, including: Micro-MEC, AR/VR, 5G MEC edge stack accelerated with SmartNICs, and more. For the hackathon competition, we also featured a top prize of  $1000 and $500 for the runner-up teams. Please read on below for feedback from participants and details for the winning teams – Team Planet (1st), Team BlueHat (2nd), Team Blaz3r (3rd) and Team grind (3rd-tie).

“It was a day trip to San Diego to attend the Akraino 5G MEC Hackathon. I was excited when I entered the conference room in Qualcomm campus. Honestly, I never expected so many people. There were people from all over the world gathered in the room, which made it look and feel crowded in a good way with lots of enthusiasm radiating from everyone. What made me more surprised is that I saw a lot of college students. As an open-source project and cutting -edge (oh yes, edge!) technology, we really need the fresh blood! These students really have a lot of good ideas of how to prosper our edge computing platform, surveillance, IoT automotive, they bring creative and inspiring scenarios to the popular applications cases for MEC. Also, the hackathon is a good platform for people in the industry to change ideas on edge, I know a lot of people and companies got the chance to collaborate through this event. As a sponsor, CMTI (China Mobile Technology USA) also get a lot of good ideas and partners. I have to say it was a wonderful day!” – Su Gu, CMTI 5G ICSV

Some highlights on the winning teams are below.

1st Prize: Team Planet

Participating in Akraino 5G MEC Hackathon is an extraordinary experience for us.

After brainstorming at the beginning, we decided on the direction of our exploration: adopting the edge computing paradigm to mitigate the privacy issue of surveillance in the smart city. The foundation of smart city applications is the enormous amount of data collected from physical space. However, pervasive sensing also raises privacy concerns as the collected data may be highly sensitive. Even worse, the massive adoption of cloud computing in smart city applications makes sensitive data generally processed by the untrusted service provider on untrusted infrastructure. We argue that edge computing is capable of mitigating existing privacy issues as it could provide a different trust model to the smart city applications.

To instantiate our thought, we designed the driven scenario as a privacy-preserving video surveillance application in a meeting room. Video surveillance is commonly used in mission-critical spaces for security and safety purposes, like theft protection, environmental safety monitoring, and emergency response. However, on the other hand, video footage of public physical space is also highly sensitive. Residents are usually reluctant to let the video footage be reviewed or stored unless there is a real emergency or anomaly. So we designed our application, which first sends captured video to trust edge infrastructure to detect if there is an abnormal situation. Only the photos reflect the anomaly will be shared with the space manager on the cloud and be stored. In our proof-of-concept prototype, we define the abnormal condition as higher-than-expected occupancy in a room.

To implement the prototype, we leveraged the edge computing platform provided by MobiledgeX. It gives us a convenient way to deploy a containerized application to an edge infrastructure nearby. We deployed an open-source face recognition at the edge. We then implemented a Python program on a laptop to make it function as a video surveillance camera by using its webcam. The laptop keeps capturing the pictures, sending them to the edge, and calling the face detection algorithm to count the people in the room. If the occupancy is higher than a certain threshold, the image is sent to the cloud and stored. Otherwise, the program drops the image to protect residents’ privacy.

During the final review and judging phase, judges and audiences gave a lot of helpful comments and feedback. We together discussed topics like the scenarios that edge infrastructure is trusted, the capability of enhancing this application using trusted hardware, and how to extend this use case to other situations like controlling the activation of voice assistants.

In this hackathon, we not only learned more knowledge about edge computing but also got hands-on experience on real-world edge computing platforms and opportunities to build connections to the open-source community. Thank you, Akraino, for hosting this fantastic hackathon event. Thank you, Vikram and Bruce from MobiledgeX, for providing the edge computing platform and all the kind supports. Finally, a big thank you to everyone in this hackathon, for sharing your brilliant ideas and insights. We hope there will be more events like Akraino 5G MEC Hackathon that provides students opportunities to learn more about critical and cutting-edge technologies.

2nd Prize: Team BlueHat

When four of us read through the hackathon prompt, we thought to ourselves: how could we leverage a smart city’s sensor network to produce real impact? Our experience living in the city drew our attention to city traffic: very often we see an emergency vehicle, such as a fire truck and an ambulance, getting stuck at a red light behind a long line of cars. If the line was short, cars in front would notice the emergency vehicle behind and would actively run the red light to let the emergency vehicles pass the intersection. However, running a red light is inherently dangerous. In addition, when the line of cars becomes long under heavy traffic, the cars in front would often not be able to notice the emergency vehicles stuck way back. Therefore, we realized that an infrastructure-level solution is needed and developed Smart-city Emergency Express (S.E.E.), a traffic control system for smart cities. Using S.E.E., traffic lights can actively detect emergency on the streets and if those vehicles are found, they automatically switch to green lights for them to pass. The overall hackathon experience was exciting and fun. We have posted our code on Github. Thank you Akraino for the recognition of our work and hosting this meaningful hackathon! – Team BlueHat

3rd Prize (tie): Team TrailBlaz3r

It’s obvious that starting from years ago, the growth personal vehicles has exploded exponentially. As we progress into the future, the problem will only get worse because there are always more new cars than scraped cars. With this problem comes the challenges of parking, especially in the more densely populated area. For example, in major european, asian and north american cities, cars are all over the side of the streets and is extremely difficult to find parking. With the uprising of 5G as well as this device, we envision a situation where all the parking spots are being recorded and regulated such that you would always know, in which area of vicinity there is parking. It is applicable to mall’s parking structure. As we know, parking space indicators are individually placed for each parking spot. Therefore, it’s inefficient because of the amount of sensoring device required. With 5g technology, real-time parking availabilities are viable through prediction model and they could be sent to modile devices so that customers could have first hand information about uhe availability of parking spot. Additionally, with the upcoming of autonumous car, it would be also great for guiding cars without human onboard, to certain parking area in case there is no parking near the driver’s leaving point. These traffic/parking availability information could also be sold to data broker for specified needs.

3rd Prize (tie): Team Grind

On seeing a Facebook post about a hackathon in Qualcomm, San Diego, I was naturally inclined to attend it considering the proximity and value addition it had to offer. After treating ourselves to cookies and coffee, we began brainstorming approaches to solve a problem related to smart cities. After going through the slides and evaluating our options, we finally decided to develop an air quality analytics system. We developed a comparative model between Los Angeles and San Diego to explore possibility of location-specific alert generation system for air quality standards. We learnt the importance of edge-computing and familiarized ourselves with the latest technologies in different companies at the hackathon – Arm, China Mobile etc. I connected with wonderful people like Tina Tsou and Robert Wolff, whom I had the pleasure of meeting again at the Arm IoT Dev Summit in Mountain View, California on Dec 2-3rd, 2019. I hope to stay in touch with the community and contribute towards furthering technology on the edge. ~Nitish Nagesh, 2nd year CSE master student, UC San Diego

For more information about Akraino, visit the wiki page. Stay tuned here for more details about new hackathons and meetings for the Akraino project and other LF Edge projects!

LF Edge in 2020: Looking back and Revving forward

By Akraino Edge Stack, Baetyl, Blog, EdgeX Foundry, Fledge, Home Edge, Open Glossary of Edge Computing, Project EVE

Written by Melissa Evers-Hood, LF Edge Governing Board Chair 

Dear Community,

Happy New Year! As we kick off 2020, I wanted to send a note of thanks and recognition to each of you for a wonderful 2019, which marked several meaningful accomplishments for this organization.  LF Edge was launched in Jan 2019 with an aim to unify the edge communities across IOT, Telco, Enterprise and Cloud providing aligned open source edge frameworks for Infrastructure and Applications.

Our accomplishments include:

  • EdgeX Foundry has blossomed this year in participation, downloads, and use cases. EdgeX, as folks commonly call it, also graduated to Impact project stage and surpassed 1.5 million container downloads in 2019.
  • Akraino, which also reached Impact stage this year, is preparing for it’s second release with 5 new blueprints for R2, with updates to 9 of the existing 10 R1 blueprints already released. Most notably, its broadening its blueprint profile to include new blueprints for Connected Vehicles and AR/VR, truly becoming a viable framework across edge applications.
  • At the Growth Stage, Open Glossary provides common terminology and ecosystem mapping for the complex Edge environment. In 2019, the Glossary Project shipped 2.0 of the Glossary, which was integrated into the 2020 State of the Edge Report. The Glossary Project began the process of helping to standardize terminology across all LF Edge projects, and also launched the LF Edge Landscape Project: https://landscape.lfedge.org/.
  • Also at the Growth Stage, Project Eve allows cloud-native development practices in IOT and edge applications. EVE’s most recent release, 4.5.1 (which was gifted on December 25, 2019), provides a brand new initramfs based installer, ACRN tech preview, and ARM/HiKey support.
  • The Home Edge project, targeted to enable a home edge computing framework, announced their Baobab release in November. The Home Edge Project has initiated cross-project collaboration with EdgeX Foundry (secure data storage) and Project EVE (containerized OS).
  • We also added 2 additional projects this year.
    • Baetyl which provides an open source edge computing platform.
    • Fledge which is an open source framework and community for the industrial edge focused on critical operations, predictive maintenance, situational awareness and safety. Fledge has recently begun cross-project collaboration with Project EVE and Akraino, with more information available here.
  • Our reach has broadened with 9k articles, almost 50k new users, and 6.7M social media impressions.

I am excited about the work ahead in 2020, especially as we celebrate our one year anniversary this month. We laid the foundation last year – offered a solution to unite the various edge communities – and now, with your support and contributions, we’re ready to move to the next phase.

LF Edge is co-hosting Open Networking & Edge Summit in April and our teams are working hard on several cross-project demos and solutions. We’re planning meetups and other F2F opportunities at the show, so this conference will be a must.

Our focus as a community will be to continue to expand our developers and end users.  We will do this through having agile communities, that collaborate openly, create secure, updateable, production ready code, and work together as one. We also expect that there will be new projects to join and integrate.  As we walk into this bright future, working as a unified body will demonstrate that the fastest path to Edge products is through LF Edge.

I look forward to working with each of you in ‘20 and seeing you in Los Angeles this April at ONES!

Melissa

EdgeX Foundry Launches China Project

By Blog, EdgeX Foundry

Written by Gavin Lu, LF Edge member, EdgeX Foundry China Project Lead and R&D Director in the VMware Office of the CTO

LF Edge’s EdgeX Foundry recently launched a China Project, which includes but is not  limited to evangelism, engineering and marketing of EdgeX features, use cases, productions and solutions. Everyone is welcome, and all presentations and notes will be openly posted on the Wiki.

To kick it off, VMware recently hosted an EdgeX Foundry Meetup and a China Project F2F.  During the EdgeX Foundry meetup, eight speakers presented topics to about 100 attendees from Arm, China Telecom, China Mobile, China Unicom, ZTE, Redhat, Oracle, Wind River, Siemens, Advantech, SAIC, Suning, Yonyou, Oppo, Unigroup, GIT, BUPT, and a few universities and startups.

  • Alan Ren, MSD of VMware China R&D, welcomed attendees and presented the agenda
  • Xuan Yang, Director of LF China: “Using Open Source: Building an Enterprise IoT Platform Based on Linux Foundation Open Source Projects
  • Gavin Lu, R&D Director of VMware: “The Development History, Status Quo, and Future of EdgeX Foundry China Community”
  • Melvin Sun, Sr. BD Manager of Intel IoT: “Intel Open Retail Initiative.”
  • Rocky Jin, Product VP of EMQ: “Kuiper-open source edge real-time streaming data analysis framework”
  • Haihua Chen, WayClouds CEO: “EdgeX Foundry-based AIoT Cloud Native Edge Computing Platform”
  • Xinghui Yong, Architect of JD Retail: “Application of EdgeX in JD Star Retail IoT Platform”
  • Xiaojing Xu, Architect of Thundersoft: “Thoughts during the implementation of edge computing”
  • Henry Zeng, Principle PM of AI Platform, Microsoft Aisa Engineering Institute: “Application of High-Performance Modeling Based on ONNX Runtime in Edge AI”

The Workshop

As part of the meetup, VMware also hosted a workshop, which provided a hands on opportunity to new comers or entry level developers to EdgeX Foundry, and provide an easy experience of edge application in full life cycles, from dev, test to package, publish, deploy, monitor. Another part of the workshop is to show how ML inference could be conducted easily by a set of common Rest API service support heterogenous hardware accelerators.

VMware provided full support for IT infrastructure, toolkits, application management platform and ML inference services based on our innovation projects around EdgeX Foundry. Around 55 people registered for the workshop and most attendees finished all tasks as planned.

F2F Meetup

In a smaller group of about 20 pre-registered people, VMware hosted the first China Project face-to-face meeting to prepare the 2020 plan. Sixteen representatives from 12 companies joined the discussion, including thought leaders from the Linux Foundation, VMware, Intel, Dell, JD, H3C, China Mobile, Thundersoft, EMQ, Wayclouds, Zilliz, and OriginalTek, etc.

Melvin Sun from Intel introduced the idea of China’s first EdgeX Foundry Hackathon, which triggered an engaging discussion about the date, venue, form, topics, collaboration approach, teaming topics, etc. The event is still in the planning phase, though we are hoping to host the hackathon in March.

Gavin Lu from VMware introduced the high level idea about China Project and a draft proposal on what could be done in next year. The draft plan of China Project in 2020 could be roughly divided into three categories:

  • Evangelism
    • User/solution list: List all EdgeX Foundry users and relative solutions in China project wiki page, to encourage and advocate its usage.
    • Webinars: Keep (increase if necessary) the bi-monthly frequency, focus more on EdgeX app developers, in code level and architecture analysis.
    • Meetups: Plan for quarterly, or increase instances on specific industries, focus on architecture, functions, solutions and product integration.
    • Workshops: Host yearly or bi-annual, entry level code training, provide hands-on experience on EdgeX Foundry app development.
    • Hackathons: Leverage yearly or bi-annual, advanced code camp, focus on new features, projects, solutions, with sponsorship and awards.
  • Collaboration
    • Internal
      • Solutions: focus on mature industries, like retails, manufacturing, energy, cities/campus.
        • Summarize use cases and customer requirements
        • Define reference architecture models and implementations
      • Test bed/certificate: focus on edge devices, OEM vendors and e2e solutions
        • Facilitate advanced developers and distribute dev kits
        • Develop and deploy test beds to validate solutions
    • External
      • Enhance collaboration with other relative industry organizations, e.g. CAAI, AII & ECC.
      • Active discussion with telco carriers on use cases of integration with 5G, MEC and Industrial IoT
      • Build partnership with developer communities, like Go-lang community
  • Contribution
    • Encourage and assistant direct code contribution to EdgeX code repos
      • Provide help to interesting organizations, on code review, bridging connections, communications etc.
    • Organize translation of English docs to Chinese, or write tech posts in Chinese directly.

We have to build sub-teams to execute action items accordingly. With volunteering from representatives, industry sub teams were built with team leaders as following:

  • Retail: Intel*, JD, Thundersoft, WayClouds, Dell, Zilliz, China Mobile
  • Manufacturing: H3C*, Quarkdata, Dell, Thundersoft, Intel, China Mobile
  • Energy: WayClouds*, Quarkdata, Dell, H3C, EMQ, China Mobile
  • Cities/Campus: Intel*, Zilliz, Dell, EMQ, China Mobile
  • Transportation: OriginalTek, China Mobile

Companies with * is the team lead of that industry sub-team. Due to limited members in transportation sub-team, there is no team leader yet there. All sub teams welcome new companies to join.

As for the core team, besides VMware, all industry team leaders join, i.e. Intel, H3C, WayClouds. To ensure daily work and communication, Intel is nominated as co-maintainer for China Project.

The China project core team and all industry sub-teams will conduct discussions separately, actively attract more companies to join, and produce annual plan and action items within two months.

For more information, stay tuned to the EdgeX Foundry China Project Wiki: https://wiki.edgexfoundry.org/display/FA/China+Project. All updates will be posted there.

My ‘First’ and the ‘First’ EdgeX Open Hackathon – Infinite Possibilities

By Blog, EdgeX Foundry

Written by Sangeeta Ghangam, Platform Architect in the Retail-Banking-Hospitality-Education (RBHE) Division, Internet of Things Group, Intel

On October 7-8, 2019, I participated in the first LF Edge EdgeX Open Hackathon focused on Retail use cases. I had some exposure to EdgeX Foundry before the hackathon but it definitely did not prepare me for the experience that lay ahead. I normally prefer planning my work travel & technical sessions to the point where I know exactly what’s on the agenda, what needs to be done prior to the session and how it can all come together. However, this time around, I had no clue what we were going to do and how we were going to do it. I knew a few of my colleagues were on the team but we don’t work together on most of the projects so it was difficult to know who would do what, plus we had one of our customers/partner (Intuiface) on the team as well. To top it all, pre-work was allowed but, unfortunately, we didn’t get a chance to do any before hand.

Sounds like a disaster waiting to happen, right?! But it was a perfect way to experience the hackathon. The objective of the EdgeX Open was to introduce the EdgeX Foundry infrastructure to the participants – a mix of folks from all backgrounds and expertise, for feedback both technical and from a go-to-market perspective. On the first day,  we were told about all the different software and hardware tools available for the participants – from compute systems to sensors to cameras and retail products.  We also learned more about the EdgeX Edinburgh release, which was a significant milestone for the software, available as a docker or a snap package. We spent the first 2 hours after the initial presentations just fiddling with all these different options – install EdgeX, rummage through the sensors etc. Finally, we found a camera we thought we could use in addition to the bonus camera that was setup as a mock check-out lane. Now that we got comfortable with the tools we needed a use case or a problem to provide solution for. We considered the topics or themes which were part of the hackathon, the wildcard appealed the most. And a “real” problem surfaced as well – customer friendly checkout in the age of automated & self-checkout?

At some point or another, we have all experienced frustration as we tried to self-checkout quickly resulting in delays, waiting for help, etc. We figured we could use the sensors and camera to gather data, feed it to EdgeX and generate insights that a store associate can use to provide assistance where needed. We decided to split the solution over 3 systems –  one running EdgeX, one running analytics over Intel Openvino and another running the dashboard (for the store associate) and use the following list of sensors:

  • 2 Cameras – One at our desk and the bonus camera representing the mock check-out lane
  • Nexmosphere sensor kit consisting of RFID sensors and LED sensors. We planned to use the RFID sensor to track the product at checkout and the LED sensors to provide a visual status of checkout lane to the store associate.

The multi-system and multi-sensor setup mirrors what is typically found in Retail Stores today which is where EdgeX infrastructure can work as a data highway. We split the work on the 3 systems amongst the 5 team members and started in earnest around mid-afternoon on the first day. I remember we finished 70% of the work on the first day and about 30% on the second.

We had several learnings along the way as we experienced the different software and hardware pieces:

  1. There is more than one way to install EdgeX on the target system via containers or snaps. Since we were comfortable with containers, we used the same and did not run into any significant issues during setup.
  2. We ran into some hurdles while using Ubuntu 18.04 for Intel Openvino installation. Turned out Ubuntu 18.04 changes how the mirror sites work for downloading dependencies, reinstating these settings seemed to help.
  3. It was difficult to make changes to the device profile in EdgeX to add additional variables for the new sensors we wanted to add to the system. It required multiple re-installs of the EdgeX system, I believe this is a known issue and only way to work around this is to purge the database and/or re-install.
  4. We also wanted to showcase remote management using Intel vPRO but ran into issues trying to use the snap version of the software.

We were able to work through items 1, 2 and 3 with help from the expert team from Intel but had to abandon item 4. The final solution looked like the following:

We had System 1 running camera analytics using Openvino such that any negative emotions detected in the customer were triggering a ‘1’ to the EdgeX  MQTT device service. We added two additional device services to receive product information via the bonus camera setup (this was the surprise element in the hackathon and had bonus points if included in the solution) and the RFID sensor. The dashboard created using Intuiface REST API tools enabled a real time view of the sensors. Depending on the product and the customer emotion analysis it would provide real time chart of the check out lane. If the customer exceeded ‘x’ amount of time with neutral, disgust or anger (any negative emotion), the software on system 1 would change the data from ‘0’ to ‘1’ to the MQTT device service. The custom software we wrote to extend the device and cloud services sent this data to the Nexmosphere sensor management software so the LED’s would turn ON. Given the real time chart and the LED status, the store associate can offer to help the customer before being called to help.

On day 2, we explained our motivation behind the work to the judging team ahead of the formal presentation. It was great to hear their questions and understand their perspective, we did not realize we ended up creating a solution that could support multiple use cases. I remember we titled the work and selected the use case ‘Enhanced Customer Experience during Checkout’.

Throughout this flurry of activity, we had opportunities to network with other teams, look at some of the cool work they were doing. We also interacted with the experts from LF Edge member companies like Intel, Dell and Canonical, which gave us first hand opportunity to provide feedback towards the next revision of EdgeX. The hackathon was very well organized, had great food and even included a live music jam session on day 1!

Although it was a new venue and a new team, it all came together in the end. Team Intel/Intuiface won second place!

Stay tuned here for more details about the next EdgeX Open Hackathon! If you missed the EdgeX Open, click here to watch the video from the event.

LF Edge Member Spotlight: IOTech Systems

By Blog, EdgeX Foundry, Member Spotlight

The LF Edge community is comprised of a diverse set of member companies that represent the IoT, Enterprise, Cloud and Telco Edge. The Member Spotlight blog series highlights these members and how they are contributing to and leveraging open source edge solutions. Today, we sat down with Andy Foster, Product Director, at IOTech Systems to discuss the importance of a growing ecosystem, their IoT framework, the impact LF Edge has made and what the future holds for the company.

Can you tell us a little about your organization?

IOTech’s vision is to build and deploy the pervasive secure, open IoT software platform for edge environments that helps drive innovation, global adoption, market velocity and scale.

The company is leveraging an open source strategy based on the LF Edge’s EdgeX Foundry project to accelerate growth of a global partner ecosystem and dramatically increase deployment velocity of IoT systems by reducing custom systems integration. The EdgeX project is aligned around a common goal – the simplification and standardization of the foundation for edge computing architectures in the IoT market.

IOTech is supporting the rapidly growing EdgeX global developer community and partner ecosystem by providing a fully commercialized version of the EdgeX called Edge Xpert.

This licensed offering comes bundled with a range of industrial grade connectors to popular North and Southbound and is available on multiple hardware and OS combinations with regular software upgrades and different support and maintenance service level options. Complementary professional service offerings include training, pilot project support, accelerated product extensions and third party product integrations.

Additionally, IOTech has extended  EdgeX with its recently announced Edge XRT, the first “hard” real-time edge IoT platform.

Edge XRT is designed to meet the needs of industrial edge applications faced with one or more of the following key challenges: deployable on ultra-low footprint embedded edge nodes; latency and response times measured in microseconds; requirement for predictable real-time processing and execution.

Why is your organization adopting an open source approach?

IOTech’s core business execution strategy is to support an open source business model. We believe that this is the only model that can realistically facilitate rapid global scale out of this technology in the window of opportunity that exists, both in terms of removal of barriers to development, deployment and Time to Market (TTM) for new products and services. IoT is also fundamentally about managing heterogeneity we believe that the market is demanding an ‘open’ versus proprietary approach at the platform level, our customers ultimately want choice of best of breed, not to be tied to one vendor’s solution.

Why did you join LF Edge and what sort of impact do you think LF Edge has on the edge, networking, and IoT industries?

We believe that the best way to address market fragmentation and drive edge technology adoption is through industry collaboration and an open architecture approach. LF Edge is creating an ecosystem of companies focused on addressing the key challenges faced by the next generation of edge systems.

LF Edge membership is growing rapidly and includes a broad spectrum of companies from major international technology leaders to new startups. The breadth of membership and expertise is helping to ensure a cross-industry approach, with organizations working collaboratively to solve a common set of edge related problems. By avoiding duplication while at the same time ensuring interoperability and re-use across LF Edge projects is key to speeding time to market and reducing the implementation risk of new edge technologies. 

What do you see as the top benefits of being part of the LF Edge community?

Firstly, by collaborating with other organizations on the development new open source edge technologies allows companies to pool resources and leverage the collective expertise of many of the world’s leading technology providers. For IOTech, this has the significant benefit of enabling us to bring new products to market more quickly and share the costs of developing these solutions.

Secondly, LF Edge is helping to shape the future direction of edge computing and being part of the ecosystem gives IOTech the ability to help influence that direction, something that is much more difficult to do if we were not a member. It also gives us much better visibility into the where the industry and market is moving with respect to edge computing technologies, as well as access to some of the best brains driving this change.

Finally, being part of growing LF Edge  ecosystem provides IOTech with many commercial opportunities to partner with other member companies to collaborate on new projects and drive business growth.

What sort of contributions has your team made to the community, ecosystem through LF Edge participation? 

IOTech are one of the founder members of the EdgeX Foundry project and have been actively participating in the project at various different levels from it’s inception. We have made significant contributions in terms of technical leadership and code contributions within the project. Members of the IOTech team currently hold the following leadership positions within EdgeX:

  • Keith Steele, TSC Chair and LF Edge Board Member
  • Jim White, TSC Vice Chair
  • Iain Anderson, Device Service WG Chair
  • Robin Chatterjee, Test/QA WG Chair

We have leveraged our expertise in OT systems to work extensively on EdgeX’s Device Service layer. This work includes the development of SDKs in Go and C and the implementation of a number of protocol specific Device Services including Modbus, BACnet, OPC UA, MQTT and Virtual.

As TSC Vice chair and original EdgeX architect, Jim White has been active across all of the project’s WGs, providing technical leadership and support to the EdgeX teams.  For almost three years Keith Steele has been Chair of the TSC, helping to coordinate the projects direction and actively promote its goals and objectives within the EdgeX ecosystem and wider industry.

In addition to IOTech’s contributions to EdgeX Foundry we are also participating other complementary LF Edge projects such as the Akraino Time-Critical Edge Compute project where our EdgeX experience can be shared within the wider LF Edge ecosystems.

What do you think sets LF Edge apart from other industry alliances?

Put simply delivery focus! Other bodies are focused on producing guidelines and possibly new edge standards, whereas LF Edge’s objective is to produce open source solutions that can be deployed in real system or proven blueprints that can be used to support real edge use cases. 

How will  LF Edge help your business?

Firstly, the collaborative development that is inherent in a open source project is allowing  IOTech to leverage a far larger pool of development resources than is currently possible on our own. This is helping us to bring new edge solutions to market more quickly.

Working within an ecosystem of the world’s leading-edge technology companies ensures that the technologies that we develop are addressing the real needs of industry. It provides our customers with the reassurance that our products were developed with broad industry support, helping reinforce the importance of openness and choice.

Finally, from a marketing perspective the profile of LF Edge generates a lot of attention in our target markets and the efforts of the LF marketing team provides member companies with lots of opportunities to complement their own marketing programs and also share costs, for example by attending key industry tradeshows as a co-sponsor on the LF Edge booth.

What advice would you give to someone considering joining LF Edge? 

From IOTech’s perspective we’ve hopefully outlined the key benefits of joining LF Edge. We also think that these benefits will apply to most organizations. Our recommendation is to join, embrace collaboration and most importantly get involved. Your return on investment will be multiplied depending the effort you apply and the projects that you support. Where else can a company leverage the combined expertise in edge computing and resources of the LF Edge ecosystem, especially when combined with the many commercial opportunities for collaboration and partnering.