ISSIP Ambassadors, Marialuisa Saviano from the University of Salerno, Italy, Paul Maglio from the University California Merced, USA, and Mohamed Zaki from the University of Cambridge, UK will get together and explore the Sustainability of Service Systems on May 3 at 15h30-16h00 BST / 7h30-8h00 PT. The session will be moderated by ISSIP Board of Director and Co-Founder, Jim Spohrer.

The panelists are thought leaders in sustainability in service science, and the session is expected to offer an insightful discussion. You can find more info about the session and register here

ISSIP announced the winners of ISSIP 2023 Excellence in Service Innovation Awards. ISSIP congratulated Luna Zia, Inc for Overall Impact of its Work to Business, Society, and Innovation.

Luna is the word’s first standard for BLE-cloud communications. It is secure. It is bi-directional. It should have been devised ten years ago at the same time beaconing was introduced and indeed many have implemented BLE-to-cloud communication verticals but none have tried or succeeded in developing a standard that makes this connectivity open to (almost) any device and any application.

The Award for Impact to Business went to IBM’s Robotics Solutions for Asset Performance. The IBM team explains that their solution offers an entirely new market and service, which combines the state of the art agile robots with the latest AI capabilities from IBM Research. The solution moves data from the edge to the cloud in a secure way that will meet the standards of IT organizations, as these solutions move toward full operational adoption.

The Award for Impact to Innovation went to a joint project led by the University of Virginia, Warwick University, and New York University. Their joint study is about the first in-depth, longitudinal investigation of how ML-based prediction tools are used for medical diagnosis decision-making. AI tools may operate in similar ways technologically, but they are experienced in unique ways, depending on users, context, and work practices. This is a fundamentally new way to think about opacity and has implications for how ML tools are designed and deployed in critical decision-making contexts.

More info on the Awardees can be found here. The presentations from Award Winners and their presentation slides will be uploaded to ISSIP Youtube channel and ISSIP Slidehshare.

The ISSIP Excellence in Service Award is given to a company or organization that has designed, developed, or deployed a novel solution that, in the judgement of, the ISSIP Awards Committee, is the most innovative of all the submissions for that year in its category. Submissions undergo rigorous evaluation by ISSIP’s Award Committee, composed of experts from industry and academia that are not affiliated with the submitting companies. Submissions are judged by scoring on the uniqueness, creativity, technical merit, value generation and impact of the innovative solution in each of three categories: ‘impact to business’, ‘impact to society’, and ‘impact to innovation’.

As I have expressed my interest to step down as an Editor-in-Chief, ISSIP is looking for a Chief Digital Content Program Manager who can take over my role. If you have a keen interest in donating your time and skills to help ISSIP generate digital content and disseminate them across the ISSIP community and beyond, please get in touch with your CV at volunteer@issip.org. You can find detailed job description here.

ISSIP Ambassador Lead, Christine Ouyang, has kindly contributed to the April newsletter’s guest article.

By Dr. Christine Ouyang
Estimated Reading Time: 4 minutes

Edge computing is a distributed computing paradigm in which data processing and decision-making occur at or near the data source. Let me explain in a simple language. If a centralized data center or cloud is our brain, the edge is our limbs, ears, eyes, nose, tongue, and/or skin. While sophisticated neural processing occurs at the lowest level of our motor hierarchy when we withdraw our hand from a hot iron, the “Automatic” reflex enables us to act quickly to protect ourselves from burning without us having to think about it consciously in our brain. Similarly, in edge computing, computing resources such as servers and storage are placed closer to the devices and sensors that generate data to allow for real-time or near-real-time information processing, decision-making, and action-taking. Some of the key advantages of edge computing include fast responses, reduced latency, improved data security and privacy. These advantages attribute to the ability of edge computing to manage, store, and process a large amount of data that is often sensitive at the edge rather than transmitting it to centralized data centers or cloud.

Just as the reflex can be modulated by higher levels of our motor hierarchy, edge computing can be regulated or modulated by cloud computing. For example, an artificial intelligence (AI) model can be trained and maintained in the cloud. The model is then deployed to thousands and hundreds of thousands of endpoints (for example, the Internet of Things (IoT) devices) at the edge for inferencing. This contrasts with Federated AI where the model is trained at the edge without aggregating the data to the central cloud environment.   In the continuum from edge to cloud, there could also be regional data centers or network edge or edge cloud acting as our peripheral nerve systems and spinal cord for relaying signals (such as policies, data, and models) and making decisions.

Edge computing may sound like a complex concept, but its superior ability to offer low latency and enhanced data security means that it could be widely used with many emerging technologies, such as IoT, AI, robotics, digital twins, and 5G, to name a few. It is also noticeable from a growing number of use cases of edge computing that many businesses have started to leverage edge computing to improve safety, efficiency, and customer experiences. Some of the examples include data-intensive and time-critical applications for autonomous vehicles, industrial automation, healthcare, personalized experience in retail, smart home/building/cities/nations, virtual reality, and augmented reality. However, most edge solutions today are highly customized or First-Of-A-Kind (FOAK) for each individual use case, making them difficult to scale.

The market adoption for edge computing is growing at a phenomenal rate, but to amplify its impact on business and society, we may need to come up with innovative approaches that effectively supports the growing adoption across many industries. For example, we may consider build the ability to manage the fragmentation of systems and standard caused by edge computing; the ability to create edge platforms or solutions that can be consumed as services so that they scale up across different industries; and the ability to extend edge computing as a holistic and horizontal technology for efficient use of resources that results in reduced operational cost. Moreover, the advanced standardization in edge computing would improve its interoperability, which, as a result, could enable its integration with other devices and systems more seamlessly.

Finally, when I think of skills for the future, we need a broad set of skills and expertise for edge computing, including networking, IoT, programming, cloud computing, security, data management, AI and even Blockchain, which makes my brain hurt!