UMBRELLA: A One-stop Shop Bridging the Gap from Lab to Real-World IoT Experimentation

• URL: http://arxiv.org/abs/2401.14829v2
• Date: Fri, 2 Feb 2024 13:25:13 GMT
• Title: UMBRELLA: A One-stop Shop Bridging the Gap from Lab to Real-World IoT Experimentation
• Authors: Ioannis Mavromatis and Yichao Jin and Aleksandar Stanoev and Anthony Portelli and Ingram Weeks and Ben Holden and Eliot Glasspole and Tim Farnham and Aftab Khan and Usman Raza and Adnan Aijaz and Thomas Bierton and Ichiro Seto and Nita Patel and Mahesh Sooriyabandara
• Abstract summary: UMBRELLA is an open, large-scale IoT ecosystem deployed across South Gloucestershire, UK. It is intended to accelerate innovation across multiple technology domains. Key features include over 200 multi-sensor nodes installed on public infrastructure, a robotics arena with 20 mobile robots, and a 5G network-in-a-box solution.
• Score: 35.108720391825244
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: UMBRELLA is an open, large-scale IoT ecosystem deployed across South Gloucestershire, UK. It is intended to accelerate innovation across multiple technology domains. UMBRELLA is built to bridge the gap between existing specialised testbeds and address holistically real-world technological challenges in a System-of-Systems (SoS) fashion. UMBRELLA provides open access to real-world devices and infrastructure, enabling researchers and the industry to evaluate solutions for Smart Cities, Robotics, Wireless Communications, Edge Intelligence, and more. Key features include over 200 multi-sensor nodes installed on public infrastructure, a robotics arena with 20 mobile robots, a 5G network-in-a-box solution, and a unified backend platform for management, control and secure user access. The heterogeneity of hardware components, including diverse sensors, communication interfaces, and GPU-enabled edge devices, coupled with tools like digital twins, allows for comprehensive experimentation and benchmarking of innovative solutions not viable in lab environments. This paper provides a comprehensive overview of UMBRELLA's multi-domain architecture and capabilities, making it an ideal playground for Internet of Things (IoT) and Industrial IoT (IIoT) innovation. It discusses the challenges in designing, developing and operating UMBRELLA as an open, sustainable testbed and shares lessons learned to guide similar future initiatives. With its unique openness, heterogeneity, realism and tools, UMBRELLA aims to continue accelerating cutting-edge technology research, development and translation into real-world progress.

Related papers

• IoT-LM: Large Multisensory Language Models for the Internet of Things [70.74131118309967]
  IoT ecosystem provides rich source of real-world modalities such as motion, thermal, geolocation, imaging, depth, sensors, and audio. Machine learning presents a rich opportunity to automatically process IoT data at scale. We introduce IoT-LM, an open-source large multisensory language model tailored for the IoT ecosystem.
  arXiv  Detail & Related papers  (2024-07-13T08:20:37Z)
• CROSSCON: Cross-platform Open Security Stack for Connected Devices [4.854270243829224]
  The proliferation of Internet of Things (IoT) embedded devices is expected to reach 30 billion by 2030. CROSSCON aims to tackle current IoT challenges by developing a new open, modular, and universally compatible IoT security stack.
  arXiv  Detail & Related papers  (2024-06-05T16:03:40Z)
• Networking Systems for Video Anomaly Detection: A Tutorial and Survey [56.44953602790945]
  Video Anomaly Detection (VAD) is a fundamental research task within the Artificial Intelligence (AI) community. This article offers an exhaustive tutorial for novices in NSVAD. We showcase our latest NSVAD research in industrial IoT and smart cities, along with an end-cloud collaborative architecture for deployable NSVAD.
  arXiv  Detail & Related papers  (2024-05-16T02:00:44Z)
• Past, Present, Future: A Comprehensive Exploration of AI Use Cases in the UMBRELLA IoT Testbed [2.869828948720087]
  UMBRELLA is a large-scale, open-access Internet of Things ecosystem. This paper provides a guide to the implemented and prospective artificial intelligence (AI) capabilities of UMBRELLA in real-world IoT systems.
  arXiv  Detail & Related papers  (2024-01-24T10:17:59Z)
• MultiIoT: Benchmarking Machine Learning for the Internet of Things [70.74131118309967]
  The next generation of machine learning systems must be adept at perceiving and interacting with the physical world. sensory data from motion, thermal, geolocation, depth, wireless signals, video, and audio are increasingly used to model the states of physical environments. Existing efforts are often specialized to a single sensory modality or prediction task. This paper proposes MultiIoT, the most expansive and unified IoT benchmark to date, encompassing over 1.15 million samples from 12 modalities and 8 real-world tasks.
  arXiv  Detail & Related papers  (2023-11-10T18:13:08Z)
• Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges [55.82853124625841]
  Artificial General Intelligence (AGI) possesses the capacity to comprehend, learn, and execute tasks with human cognitive abilities. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the Internet of Things. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education.
  arXiv  Detail & Related papers  (2023-09-14T05:43:36Z)
• Tactile based Intelligence Touch Technology in IoT configured WCN in B5G/6G-A Survey [8.604882842499208]
  This study proposes an intelligent touch-enabled system for B5G/6G and IoT based wireless communication network that incorporates the AR/VR technologies. The tactile internet and network slicing serve as the backbone of the touch technology which incorporates intelligence from techniques such as AI/ML/DL. It is anticipated for the next generation system to provide numerous opportunities for various sectors utilizing AR/VR technology in robotics and healthcare facilities.
  arXiv  Detail & Related papers  (2023-01-11T06:39:07Z)
• FaRO 2: an Open Source, Configurable Smart City Framework for Real-Time Distributed Vision and Biometric Systems [1.1060425537315086]
  FaRO2 is a unified biometric API harness that allows for seamless evaluation, deployment, and simple pipeline creation for biometric software. FaRO2 provides a fully declarative capability for defining and coordinating custom machine learning and sensor pipelines. Because much of the data collected in a smart city contains Personally Identifying Information (PII), FaRO2 also provides built-in tools and layers to ensure secure and encrypted streaming, storage, and access of PII data across distributed systems.
  arXiv  Detail & Related papers  (2022-09-26T18:52:53Z)
• Learning, Computing, and Trustworthiness in Intelligent IoT Environments: Performance-Energy Tradeoffs [62.91362897985057]
  An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications. This paper provides a state-of-the-art overview of these technologies and illustrates their functionality and performance, with special attention to the tradeoff among resources, latency, privacy and energy consumption.
  arXiv  Detail & Related papers  (2021-10-04T19:41:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.