International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC)ijasuc
International Journal of Ad hoc, sensor & Ubiquitous Computing (IJASUC) is a bi monthly open access peer-reviewed journal provides excellent international forum for sharing knowledge and results in theory, methodology and applications of Ad Hoc & Ubiquitous computing. Current information age is witnessing a dramatic use of digital and electronic devices in the workplace and beyond. Ubiquitous Computing presents a rather arduous requirement of robustness, reliability and availability to the end user. Ad hoc, Sensor & Ubiquitous computing has received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational applications in real life.
The document discusses the Internet of Things (IoT) and provides an overview of some key concepts. It defines IoT as connecting billions of devices by 2020 and describes examples like Nest products and smart refrigerators. It also covers basic microelectronics, the .NET Micro Framework for programming microcontrollers, and how to connect devices to the internet using gateways.
M2M technology allows machines and devices to communicate with each other without human intervention. It uses sensors, wireless networks, and the internet to connect devices. There are four basic stages to most M2M applications: data collection, data transmission over a network, data assessment, and response to the available information. M2M has many applications including security, transportation, healthcare, manufacturing, and the automotive industry. In particular, vehicle-to-vehicle communication through technologies like DSRC can help avoid road accidents by warning drivers of dangerous conditions.
This document provides an overview of Internet of Things (IoT), including what IoT is, its advantages, common layers and protocols, applications, and challenges. The key points are:
IoT refers to physical objects embedded with sensors, processing, and software that can connect and exchange data over networks. Its advantages include ubiquitousness, device interoperability, and real-time access. Common layers are sensors, compressive sensing, protocols like MQTT, and hierarchies from edge to cloud. Popular applications areas are smart cities, healthcare, industry, agriculture, and more. Challenges to IoT include limited battery life, vulnerable sensors, connectivity issues, and security threats.
International Conference on Cryptography and Blockchain (CRBL 2021)ijasuc
International Conference on Cryptography and Blockchain (CRBL 2021) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cryptography and Blockchain.
This document discusses implementing IOTA solutions on embedded devices for Internet of Underwater Things (IoUT) systems. It presents the IOTA Tangle and Masked Authenticated Messaging (MAM) as supporting technologies. It then describes the methodology of performing a feasibility study, reverse engineering the workflow, and implementing a pure C version to integrate with embedded environments. Test results show execution times for fetching data and code size. The document concludes the proposed solution enables IoUT and outlines future work including optimization and additional IOTA features.
Call for papers - 11th International Conference on Ad hoc, Sensor & Ubiquitou...ijassn
11th International Conference on Ad hoc, Sensor & Ubiquitous Computing (ASUC 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Ad Hoc & Ubiquitous computing. Current information age is witnessing a dramatic use of digital and electronic devices in the workplace and beyond. Ubiquitous Computing presents a rather arduous requirement of robustness, reliability and availability to the end user. Ad hoc, Sensor & Ubiquitous computing has received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational applications in real life.
Internet of Things or simply IoT is a technology which are having lot of advantages in building smart systems. The meaning of IoT is where things communication and share data among each other. IoT has lots of applications.
Microsoft's view of the Internet of Things (IoT) by Imran ShafqatAllied Consultants
Credits to Imran Shafqat, an x-colleague who presented this in the Allied Consultants office and then in MIC in Lahore
More IoT blogs on http://www.alliedc.com/blog/core-services/application-integration/iot/
This document discusses Internet of Things (IoT) concepts including definitions and frameworks. It describes IoT as physical objects communicating over the internet using sensors, controllers and connectivity. A conceptual framework outlines data flow from sensor collection to analysis across six levels. Examples like a smart umbrella are provided. Reference architectures like Cisco's seven-layer model and Oracle's IoT architecture are examined, outlining their approaches to device, network and application functions in IoT. The document aims to provide an overview of key IoT concepts, frameworks and architectural views.
This document summarizes an Internet of Things (IoT) meetup that covered various topics:
- Introduction to IoT and how objects can transfer data over networks.
- Introduction to cloud computing and how resources are shared over the internet.
- IoT architecture including things, gateways, and networks/cloud.
- IoT gateways like Raspberry Pi that interface devices and cloud.
- Sensor interfaces like XBee and RS-485 that connect to gateways.
- Network interfaces like WiFi and GPRS to connect gateways to cloud.
- Cloud architecture models from various sources.
- Data acquisition from devices using open-source Ponte software.
- Data storage
The document discusses the Internet of Things (IoT). It describes the key elements of an IoT architecture as including connected devices that generate data, an aggregator device that acts as an internet gateway, a cloud service that logically aggregates devices for users, communication protocols, an access system for users, and security. It also lists several application areas for IoT, such as agriculture, automotive, construction, health, and more. Example use cases are automated tractors, self-driving cars, smart buildings, wearables, and predictive maintenance.
The Internet of things (IOT) is the network of devices, vehicles, and home appliances that contain electronics, software and connectivity which allows these things to connect, interact and exchange data
This document summarizes a pitch for providing security solutions for smart metering and smart grids. It outlines the context and need for privacy and security measures to enable distributed applications in smart grids while protecting personal data. The research goals are described as enabling privacy-preserving data collection, secure infrastructure for authentication, integration of payment methods, low-power security for in-home devices, and providing legal frameworks for remaining privacy risks. Partners are sought among vendors, manufacturers, service providers, and software companies active in this domain.
The document discusses several challenges and opportunities related to connecting devices in the Internet of Things (IoT) to internet services and applications. It notes that while billions of devices have been connected, more can be done to utilize the data. Specifically, it addresses the need for semantic interfaces and data mining/machine learning techniques to overcome heterogeneity in integrating IoT devices with internet services and applications. Additionally, it discusses approaches for storing the large amounts of data produced and developing middleware platforms to enable new service creation and deployment on top of collected IoT information.
Vishali Bhatnagar, a 3rd year B.Tech student in Electronics and Communication Engineering at Amity School of Engineering and Technology, has selected Internet of Things (IoT) as the topic for her project. She is interested in IoT because it allows for machine-to-machine connectivity and will help develop smart cities. IoT will also become more prevalent in the next five years, with many consumer and industrial devices being connected through IoT. If selected, she intends to work hard to learn about innovations in IoT and apply it towards applications like security, data storage, reducing hardware complexity, and connecting various devices to enable easy access and transmission of data.
VEDLIoT – A heterogeneous hardware platform for next-gen AIoT applications, Jens Hagemeyer, EU-IoT Training Session on “Machine Learning at the Edge and the FarEdge”, IoT Week (online event), August 2021
EU-IoT Training Workshops Series: AIoT and Edge Machine Learning 2021_Jens Ha...VEDLIoT Project
IoT - Accelerated Deep Learning for Cognitive Edge Computing, Jens Hagemeyer, EU-IoT Training Workshops Series – “AIoT and Edge Machine Learning”, May 2021
VEDLIOT – Accelerated AIoT. Jens Hagemeyer. 2nd Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2023, Toulouse, France, January 2023
SS-CPSIoT 2023_Kevin Mika and Piotr Zierhoffer presentationVEDLIoT Project
VEDLIoT – Accelerated AIoT. Kevin Mika and Piotr Zierhoffer. CPS&IoT’2023 Summer School on Cyber-Physical Systems and Internet-of-Things, Budva, Montenegro, June 2023
The document discusses VEDLIoT, a project that aims to develop very efficient deep learning for IoT applications. It focuses on developing a scalable and heterogeneous hardware platform using accelerators like FPGAs and ASICs. The project also aims to optimize deep learning toolchains for IoT use cases in industries like industrial IoT, automotive, and smart homes. An open call was announced to allow early use and evaluation of the VEDLIoT technology.
This document provides an introduction to embedded real-time systems. It defines embedded systems as special purpose computer systems that are embedded or hidden within larger systems. Embedded systems often have constraints in areas like cost, memory, power consumption and real-time requirements. The document discusses the increasing interest and opportunities in embedded systems education and careers due to growth in microprocessor technology and the integration of computers into everyday devices and industrial systems. Key topics covered include embedded system examples, trends, and the multi-disciplinary knowledge and skills required of embedded systems designers.
The document discusses emerging trends in computer engineering, specifically focusing on the Internet of Things (IoT). It defines embedded systems and their basic components. It then discusses IoT in depth, including its characteristics, enabling technologies, communication models, protocols, issues, and applications in various domains. The document also discusses embedded processors, cloud computing, and big data analytics as relevant technologies in computer engineering.
The document provides an overview of Internet of Things (IoT) concepts, including definitions, visions, frameworks and components. It discusses the basic building blocks of an IoT system including physical objects, sensors, controllers and connectivity to the internet. It also describes diverse IoT technologies related to hardware, software, communication protocols, platforms and applications. Specific examples covered include smart homes, machine-to-machine systems, industrial IoT and smart cities.
02/2017 Santa Clara, California: Networks of autonomous devices and their imp...Frank Alexander Reusch
Direct communication between IoT devices works without central control. The use of expensive gateways is therefore not a prerequisite for IoT. Gateways are inflexible, limited in scaling and an ideal target for hacker attacks. Lemonbeat has reached with this presentation that direct device communication is taken into account in future standard "Web of Things (WoT)". WoT also needs to consider future developments. For example, the self-learning mechanism in the edge area, shown in this lecture.
An end-to-end standard oneM2M infrastructure for the Smart Home - Andre Bottaromfrancis
OSGi Community Event 2015
A new world of applications emerges in the home from the growing variety of things – devices, sensors, actuators – potentially available. Several application domains are considered, e.g., security, energy efficiency, comfort, ambient assisted living, multimedia communication. The Smart Home is slowly taking off.</p>
Several actors exploit a new technical and economic opportunity to catalyze this market. This opportunity is based on the re-use of the infrastructure that telecom operators have deployed for today classic Internet and TV services. It raises technical and business challenges: Telecom operators have to open their home infrastructure to third-party applications while guaranteeing application security and consistency to all home business actors using this infrastructure.
Telecom operators have to open APIs at least two levels of their architecture: APIs in the cloud and APIs on an embedded device environment. This end-to-end infrastructure between the home network and service platforms has also to provide security at several levels, especially a consistent access right management.
The presentation will provide a vision of an open end-to-end architecture providing APIs in the cloud and in a home box to host any application and connect to any device in the Home. Among the standard organizations and industrial alliances, oneM2M standard specifications are making a reference architecture emerge. The implementation of oneM2M standard features in OSGi technology will be detailed, especially the end-to-end access right management discriminating both applications and users when accessing devices.
This infrastructure is currently prototyped thanks to the integration of open source software bricks provided by <a>Open the Box</a>, <a>Eclipse SmartHome</a> and <a>Eclipse OM2M</a> open initiatives.
Charith Perera, Arkady Zaslavsky, Peter Christen, Ali Salehi, Dimitrios Georgakopoulos, Capturing Sensor Data from Mobile Phones using Global Sensor Network Middleware, Proceedings of the IEEE 23rd International Symposium on Personal Indoor and Mobile Radio Communications (PIMRC), Sydney, Australia, September, 2012
Design & Implementation Of Fault Identification In Underground Cables Using IOTIRJET Journal
This document describes a project to identify faults in underground cables using IoT. The system uses Ohm's law to determine the distance of a fault by measuring changes in voltage across series resistors in the cable that vary with distance. A microcontroller interfaces with an analog to digital converter to convert voltage measurements to distance readings in kilometers. When a fault occurs, the location is displayed on an LCD screen and sent over the internet via GSM to a website. The system aims to easily locate faults for repair. It was tested accurately identifying faults placed at known distances in a cable model.
The document discusses the key components of implementing an Internet of Things (IoT) system, including sensors, networks, standards, and intelligent data analysis. Sensors are used to collect device and environmental data, while networks transmit the sensor data. Standards are needed for aggregating and managing the large amounts of data. Intelligent data analysis then extracts insights from the data through techniques like artificial intelligence. Challenges include power consumption, security, interoperability, data volume and variety, and regulatory standards.
The document discusses research opportunities in wireless multimedia sensor networks (WMSN). It describes how aggregating image and sensor data over wireless networks can have applications across many fields from military to healthcare. It provides examples of research areas like wireless ad hoc networks, sensor networks, and using multimedia like images for novel solutions. The document then describes the features and applications of a WMSN equipment board that allows active experimentation across various wireless networking technologies to develop distributed applications and pervasive computing systems using sensor and image data.
This document provides an overview of edge computing, including its evolution, driving factors, architectures, applications, trends, challenges, and device management. Edge computing aims to process data closer to where it is generated in order to reduce latency and bandwidth usage. The document outlines architectures like fog computing, cloudlet computing, and multi-access edge computing. It also discusses embedded hardware platforms, applications, and presents challenges of edge computing such as network bandwidth, security, and device management.
Industrial IoT Mayhem? Java IoT Gateways to the RescueEurotech
Industrial IoT comes with great expectations for operational efficiency, promising improved asset utilization and productivity gains. IIoT challenges include reliability, security, low maintenance, long lifecycle, and integration into heterogeneous and fragmented systems. This session proposes some architectural patterns that can be leveraged to overcome these challenges. It introduces, at the center of the solution, Java-powered IoT gateways and modular IoT application frameworks such as the open source Eclipse Kura. Incorporating a live demonstration, the presentation highlights some of the latest Eclipse Kura features such as a pluggable device model for fieldbus protocols, visual data flow, and connectivity across various IoT cloud service providers.
JavaOne 2016 - Presentation by Dave Woodard and Walt Bowers
This document outlines the curriculum for an IoT and embedded systems training program. It covers topics such as embedded C, microcontrollers, sensors, communication protocols, cloud computing, IoT architectures, edge computing, machine learning, and industry use cases. Live use cases and projects are also included to provide hands-on experience with developing end-to-end IoT solutions. The training is offered at multiple levels from introductory to advanced, with longer durations covering more in-depth material.
The Internet of Things (IoT) offers many industries significant new opportunities, but it also exposes them and their customers to a host of security issues. Securing the IoT requires new ways of thinking that can defend the enterprise and its customers against attackers and privacy abuses.
Similar to Industrial Pioneers Days - Machine Learning (20)
IoT Tech Expo 2023_Micha vor dem Berge presentationVEDLIoT Project
VEDLIoT Next Generation AIoT Applications. Micha vor dem Berge. VEDLIoT Conference Track co-located with IoT Tech Expo, Amsterdam, Netherlands, September 2023
Next generation accelerated AIoT systems and applications. Pedro Trancoso. Special Session on EU Projects, co-located with Computing Frontiers 2023, Bologna, Italy, May 2023
The document outlines an agenda for a presentation on the VEDLIoT project. The agenda includes an introduction to VEDLIoT by Pedro Trancoso, a presentation on VEDLIoT Hardware Platforms by Kevin Mika, and a discussion of Performance Evaluation and Benchmarking in VEDLIoT by Mario Pormann. The VEDLIoT project aims to develop very efficient deep learning techniques for IoT applications through the use of heterogeneous hardware platforms and accelerators.
IoT Week 2022-NGIoT session_Micha vor dem Berge presentationVEDLIoT Project
This document discusses optimizing a smart home system using edge computing and machine learning. It describes using embedded accelerators like the Nvidia Jetson AGX and Xavier to distribute neural networks and machine learning models to devices around the home. These include a smart mirror, kitchen, door, and other devices. The goal is to optimize the models to increase energy efficiency and distribute the workloads across the edge devices. One focus is developing a smart mirror prototype that can recognize faces, objects and gestures using embedded accelerators like the t.RECS and u.RECS boards to analyze camera input and interact with users through voice and a virtual display.
Next Generation IoT Architectures_Hans SalomonssonVEDLIoT Project
VEDLIoT Toolchain for Efficient Deep Learning on heterogeneous hardware, Hans Salomonsson, EU-IoT Training Workshops Series – "Next Generation IoT Architectures”, November 2021
The document discusses hardware platforms and accelerators for VEDLIoT. It describes the VEDLIoT Hardware Platform as a heterogeneous, modular, and scalable microserver system that supports the IoT spectrum from embedded to edge to cloud. It then provides details on several platforms: the RECS|Box platform which uses Computer-on-Module standards to achieve flexibility and performance; the t.RECS platform optimized for local edge applications; and the uRECS embedded device platform that supports machine learning acceleration and communication interfaces. Diagrams and specifications are given for the architectures of these platforms.
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Co-design of DL Accelerators in VEDLIoT. Muhammad Waqar Azhar. Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2022, Budapest, Hungary, June 2022.
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On 8 April 2019, the High-Level Expert Group on AI presented Ethics Guidelines for Trustworthy Artificial Intelligence. This followed the publication of the guidelines' first draft in December 2018 on which more than 500 comments were received through an open consultation.
According to the Guidelines, trustworthy AI should be:
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1. Jens Hagemeyer, Carola Haumann
Industrial Pioneers Days OWL –
Machine Learning
20. April 2021
VEDLIoT - Very Efficient Deep
Learning in IoT
Teaching the IoT to learn
2. 2
Platform
Hardware: Scalable, heterogeneous, distributed
Accelerators: Efficiency boost by FPGA and ASIC technology
Toolchain: Optimizing Deep Learning for IoT
Use cases
Industrial IoT
Automotive
Smart Home
Open call
At project mid-term
Early use and evaluation of VEDLIoT technology
Very Efficient Deep Learning IoT – VEDLIoT
Call: H2020-ICT2020-1
Topic: ICT-56-2020 Next Generation Internet of Things
Duration: 1. November 2020 – 31. Oktober 2023
Coordinator: Bielefeld University (Germany)
Overall budget: 7 996 646.25 €
Consortium: 12 partners from 4 EU countries (Germany,
Poland, Portugal and Sweden) and one associated
country (Switzerland).
More info:
https://www.vedliot.eu/
https://twitter.com/VEDLIoT
https://www.linkedin.com/company/vedliot/
3. 3
Bielefeld University (UNIBI) - Coordinator
Christmann (CHR)
University of Osnabrück (UOS)
Siemens (SIEMENS)
University of Neuchâtel (UNINE)
University of Lisbon (FC.ID)
Chalmers (CHALMERS)
University of Gothenburg (UGOT)
RISE (RISE)
EmbeDL (EMBEDL)
Veoneer (VEONEER)
Antmicro (ANT)
VEDLIOT partners
5. 5
VEDLIoT Hardware Platform
Heterogeneous, modular, scalable microserver system
Different technology concepts for improving: computing power density, cost-effectiveness,
maintainability, and reliability for the full spectrum of IoT, from embedded devices over the edge
towards the cloud
x86
GPU
ML-ASIC
ARM v8
GPU
SoC
FPGA
SoC
RISC-V
FPGA
VEDLIOT Cognitive
IoT Platform
6. 6
RECS Architecture (RECS|BOX, t.RECS)
RECS Server Backplane (up to 15 Carriers)
Carrier (PCIe Expansion)
Carrier (High Performance)
e.g. GPU-Accelerator
Carrier (Low Power)
#3
#2
Microserver
(High Performance)
#1
Microserver
(Low Power)
#16
#3
#2
Microserver
(Low Power)
#1
High-Speed Low-Latency Network (PCIe, High-Speed Serial)
Compute Network (up to 40 GbE)
Management Network (KVM, Monitoring, …)
HDMI/USB
iPass+ HD
QSFP+
RJ45
Ext. Connectors
GPU SoC
FPGA SoC ARM Soc
Low-Power Microserver (Apalis/Jetson)
x86 ARM v8
High-Performance Microserver (COM Express)
FPGA SoC
High-Performance
Carrier
(up to 3 microservers)
Low-Power Carrier
(up to 16 microservers)
7. 7
Embedded Device
Supports ML acceleration
FPGA
ASIC
Communication interfaces
Wired (CAN, Ethernet, CSI)
Wireless (WLAN, LoRa, 5G)
Sensors
Camera
Environment (Temp./Hum.)
Housekeeping
RECS Architecture (µ.RECS)
Processing Unit ML Accelerator
Wireless
Communication
Sensors
Wired Communication
Module (COM HPC; NVIDIA Jetson; …)
ML Accelerator
Carrier
Low-Power
Processing Unit
8. 8
End of Moore’s law & dark silicon – Domain Specific Architectures (DSA)
Efficient, flexible, scalable accelerators for the compute continuum
Algotecture – DL algorithm + computer architecture co-design
DL Accelerators
9. 9
Enabling the rapid convergence of the fast pace innovation on the hardware and
software
Deep Learning Toolchain
10. 10
Simulation platform for IoT
Open source framework for software/hardware co-development with CI-driven testing
capabilities, as well as metrics for measuring efficiency of ML workloads
Enables development and continuous testing of VEDLIoT’s security features and its robustness
Renode is available to all project members and future users of VEDLIoT and will include a
simulated model of the RISC-V-based FPGA SoC platform developed as part of the VEDLIoT
project
11. 11
End-to-end attestation, support for execution and communication
Support for
End-to-end trust (attestation)
Secrets distribution (keys)
Machine learning (federated, streaming, …)
Requirements
Support for edge applications
Decentralised, dynamic, loosely organised
Rely on
Trusted execution environments
BFT and peer-to-peer algorithms
Blockchain concepts
VEDLIoT
app
Attestation
Pool
12. 12
Safety and robustness
Define monitors for timeliness and data quality assessment
Develop safety argumentation for adaptive solutions,
exploiting architectural hybridization
Hybrid System architecture:
• Some system components implemented
with assured reliability (as needed)
• Remaining components subject to
uncertainties and prone to failures
Safety requirements:
• Defined at design time for each operational
mode
Monitoring data:
• Collected in run-time, to allow verifying if
safety requirements are being satisfied
and trigger reconfiguration if not
Timeliness (e.g., deadline
miss detection)
Sensor data quality (e.g.,
outlier, noise detection)
Accuracy of DL systems
(e.g., anomaly detection)
13. 13
Increase safety, health and well being of residents – acceleration of AI methods for
demand-oriented user-home interaction
Use case: Smart Home / Assisted Living
14. 14
Smart Mirror as central user interface
Own mirror image can be seen normally
Intuitive control over gesture and voice
Shows personalized information
Public transportation schedule
Cafeteria offering
Football scorings/leader board
Weather
News
…
Data Privacy as the highest priority
-> Edge computation of many neural networks
Smart Mirror – Central Demonstrator for Smart Home
15. 15
Face recognition
mobilenetSSD trained on WIDERFACE dataset
Object detection
YoloV3, Efficient-Net, yoloV4-tiny
Gesture detection
YoloV4-tiny with 3 Yolo layers (usually: 2 layers)
Speech recognition
Mozilla DeepSpeech
AI Art: Style-Gan trained on works of arts
Collect usage data in situation memory
Smart Mirror – Neural Networks
16. 16
Industrial IoT – drive condition classification
Control applications need DL-based condition classification
On the edge device for low power consumption
Suggestions for control and maintenance
DL methods on all communication layers
DL in a distributed architecture
Dynamically configured systems
Sensored testbench with 2 motors
Acceleration, Magnetic field, Temperature,
IR-Cam (temperature), Current-Sensors, Torque
On / Off detection without
motor current or voltage
Cooling fault detection
Bearing fault detection
17. 17
Industrial IoT – Arc detection for DC distributions
AI based pattern recognition for different local sensor data
current, magnetic field, vibration, temperature, low resolution infrared picture
Safety critical nature
response time should be <10ms
AI based or AI supported decision made by the sensor node itself or by a local part of the sensor
network
19. 19
The fun has just started!
Follow our work!
https://twitter.com/VEDLIoT
https://www.linkedin.com/company/vedliot/
https://vedliot.eu
Be part of it
Open call at project mid-term
Allow early use and evaluation of VEDLIoT
technology
20. 20
Thank you for your
attention.
Contact
Jens Hagemeyer, Carola Haumann
Bielefeld University, Germany
chaumann@cor-lab.uni-bielefeld.de
jhagemey@cit-ec.uni-bielefeld.de