Auto-ID Labs

The Leading Academic Research Network
on the Internet of Things

Research on Disruptive

IoT Applications

Auto-ID Lab at MIT

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Research on Linked-data

and Semantic IoT

Auto-ID Lab at University of Cambridge

Research on new Business Models

and Consumer Empowerment

Auto-ID Lab at ETH Zurich / HSG

Research on RFID Core Technology

Auto-ID Lab at Fudan University

Research on Scalable

IoT Architectures

Auto-ID Lab at KAIST

Research on the Network

for IoT applications

Auto-ID Lab at Keio University

ADVANCING THE IOT FOR GLOBAL COMMERCE

The Auto-ID Labs are the leading global research network of academic laboratories in the field of Internet of Things. The labs comprise seven of the world’s most renowned research universities located on four different continents.

The labs believe that the next generation of the Internet of Things can revolutionize global commerce and provide previously unrealizable consumer benefits. The primary research partner is GS1 – a not-for-profit organization that is renowned for establishing standards for global commerce such as introducing barcodes to the retail industry almost 40 years ago. The labs aim to add the consumer to the currently B2B-oriented business model of GS1 and explore opportunities for new hardware, software, business processes and applications including Linked Open Data for Products and Services.

HISTORY

The Auto-ID Labs have a long history in the field of networked RFID and emerged from the Auto-ID Center which pioneered the term Internet of Things back in 1999. The labs also founded the world’s first conference on Internet of Things. It is now an annual gathering for researchers and thought leaders.

About Us

The Auto-ID Labs are an independent network of currently seven academic research labs that research and develop new technologies for revolutionizing global commerce and providing previously un-realizable consumer benefits. The Labs are run by the Auto-ID Labs Board of Directors which assembles the Labs research directors. Currently the board is co-chaired by Prof. Sanjay Sarma and Prof. Elgar Fleisch. The GS1/ EPCglobal Board of Governors serves as primary advisor.

Co-Chairs

Prof. Sanjay SarmaMassachusetts Institute of Technology

Director, Auto-ID Lab at MIT
Focus: Hardware, software and network, business processes and applications
Prof. Elgar FleischETH Zürich and University of St. Gallen

Focus: Understanding and designing the ongoing merge
between the physical and digital world.

Research Directors

Each Lab is run by a research director and employs several associate directors, senior and junior researchers. Altogether the Auto-ID Labs currently employ seven research directors, nine assistant directors, and more than 60 researchers on three continents.

Prof. Sanjay SarmaMassachusetts Institute of Technology

Director, Auto-ID Lab at MIT
Focus: Hardware, software and network, business processes and applications
Prof. Duncan McFarlaneUniversity of Cambridge

Director, Auto-ID Lab at Cambridge
Focus: Industrial control & automation, reconfigurable industrial systems design, analysis and synthesis of intelligent control systems, automated identification systems, track & trace Systems
Asst.-Prof. Alexander IlicETH Zurich & HSG

Director, Auto-ID Lab at ETH Zurich / HSG
Focus: Business processes and applications

Prof. Hao MinFudan University

Director, Auto-ID Lab at Fudan University
Focus: Hardware
Prof. Jun MuraiKeio University

Director, Auto-ID Lab at Keio University
Focus: Software and network
Prof. Daeyoung KimKAIST

Director, Auto-ID Lab at KAIST
Focus: Hardware, software and network

Research Partner

THE GLOBAL LANGUAGE
FOR BUSINESS

WORKING WITH GS1

The labs’ primary role is to future proof GS1 by shaping and anticipating the future. For over ten years, the labs have worked closely with GS1 and EPCglobal in the development of open standards for supply chain visibility and provided strategic guidance for several flagship projects.

Since over 40 years GS1 focuses mainly on standards for more efficient supply chains. However, with the advance of smart phones and other Internet of Things technologies, companies are increasingly forced to think beyond the point-of-sale. Our current research activities therefore focus on adding the consumer to the currently B2B-oriented business model of GS1 and exploring opportunities for Linked Open Data for Products and Services (GS1 Digital).

RESEARCH REPORT

To see some highlights of the present research for GS1 please download the full report.

DOWNLOAD HERE

RESEARCH ON KEY OPPORTUNITIES

The labs conduct long-term, strategic research that is cross-industry and relevant to stated user needs and challenges. The labs follow a rigor and relevance principle that not only aims at high ranking academic publications but also yields additional tangible assets for the GS1 community such as white papers, demos, pilots and proof of concepts.

TECHNOLOGY WATCH AND ON-GOING STRATEGIC CONSULTING

Research

The research program we pursue is as diverse as the challenges our research partners face. We divide our approximately 100 research projects into the three building blocks: Business Processes & Applications, Software & Network, and Hardware.

At the business layer we investigate business cases, applications, privacy and security aspects with a clear focus on fundamentally new business processes and industries which include payment, leasing, insurance, quality management, factory design, 3PL-managenemt, brand protection, and anti-counterfeiting amongst others. While all labs are involved in business related questions, the labs of St. Gallen/ETH, Keio, Cambridge and MIT are leading these efforts.

With respect to the software & networking building block we research the future network and system architecture which needs to support fundamental new business processes and leverage the functionality of class 2 and higher tags. Again, all labs are involved in software & network research. However, MIT, and Keio dedicate most of their resources to this.

At the hardware level we look at RF & Chip design issues and focus on (a) the development of class 2 and higher tags that might include memory, battery, sensors, and actuators, and (b) on enhancing the read rates in challenging environments. The related research projects are mainly driven by the labs at MIT, Fudan and ICU.

Publications

The Auto-ID Labs produce research results in the forms of (a) Auto-ID Labs White Papers, (b) academic publications, (c) demonstrators / pilots, (d) software packages such as simulation tools, (e) presentations at workshops, and (f) tacit knowledge within its research partners. During the Auto-ID Center years (1999-2003) we produced more than 110 Auto-ID Center research papers. They form the basis for today’s Internet of Things. The websites of the Auto-ID Labs and EPCglobal provide access to the Auto-ID Center papers.

As Auto-ID Labs we have produced more than 70 Auto-ID Lab White Papers. Some of them have already been published in well-known academic and management oriented journals and thus help to convey our thinking. All white papers can be accessed through the external query interface

2021

Schneider, T., Fuchs, K., Mayer, S., Die Datafizierung von Alltagspraktiken: Datenaktivismus als neue Verantwortung?, 10 Minuten Soziologie – Verantwortung (forthcoming).

2020

Fuchs, K., Ilic, A., Year in Review 2020, Auto-ID Labs ETH/HSG Annual Report. [PDF]

Fuchs, K., Grundmann, T., Haldimann, M., Fleisch, E., HoloSelecta Dataset: 10’035 GTIN-labelled Product Instances in Vending Machines for Object Detection of packaged Products in Retail Environments, Data in Brief (forthcoming).

Fuchs, K., Haldimann, M., Grundmann, T., Fleisch, E., Supporting Food Choices in the Internet of People: Automatic Detection of Diet-related Activities and Display of Real-time Interventions via Mixed Reality Headsets, Future Generation Computer Systems (forthcoming). [PDF]

Huebner, J., Fleisch, E., Ilic, A., Assisting Mental Accounting Using Smartphones: Increasing the Salience of Credit Card Transactions Helps Consumer Reduce Their Spending, Computers in Human Behavior (113). [PDF]

Huebner, J., Girardello, A., Sliz, O., Fleisch, E., Ilic, A., What People Focus On When Reviewing Your App – An Analysis Across App Categories, IEEE Software (forthcoming).

Fuchs, K., Haldimann, M., Zeltner, M., Ilic, A., Icon-based Digital Food Allergen Labels for Complementation of Text-based Declaration, ECIS2020. [PDF]

Marty, K., Sun, Y., Fuchs, K., Rajasekaran, P., A Low-cost Approach Towards Streaming 3D Videos of Large-scale Sport Events to Mixed Reality Headsets in Real-time, 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). [PDF]

Merian, S., Tipaldi, P., Fuchs, K., Natter, M., Redefining Price Promotions to decrease Food Waste – Sell them what they need not what they want, EMAC 2020 (forthcoming).

ALL PUBLICATIONS