WF-IoT 2014 Videos
View videos from the 2014 IEEE World Forum on Internet of Things (WF-IoT)
6-8 March 2014, Seoul, Korea
IEEE WF-IoT Session: Semantic URI-based Event-driven Physical Mashup
Sejin Chun, Jooik Jung, Xiongnan Jin, Gunhee Cho, Jinho Shin and Kyong-Ho Lee, Dept. of Computer Science, Yonsei University, Korea
Discussing IoT Information Model, Object Identification and Physical Mashup Modeling.
IEEE WF-IoT Session: UHF RFID Transmission with Soft-input BCH Decoding
Grzegorz Smietanka, Germany
Session covering RFID Communication, Forward Error Correction.
IEEE WF-IoT Session: Comparison of IEEE 802.15.4e MAC Features
Xiaolin Lu, EPS IoT Labs, Texas Instruments
Discusses sensor network applications, one of the most key technologies in the Internet of Things domain.
IEEE WF-IoT Session: Analytical Model of Adaptive CSMA-CA MAC for Reliable and Timely Clustered Wireless Multi-hop Communication
Rajavaraprasad Yerra, IIT Hyderabad & Mhrd, India; Pachamuthu Rajalakshmi, Indian Institute of Technology Hyderabad, India
Reliability and delay of a single cluster wireless network is well analyzed in the literature. Multi-hop communication over the number of clusters is essential to scale the network. Analytical model for reliability and end-to-end delay optimization for multi-hop clustered network is presented in this paper. Proposed model is a three dimensional markov chain. Three dimensions of markov model are the adaptable mac parameters of CSMA/CA. Model assumes wakeup rates for each cluster. Results show that reliability and delay are significantly improved than previous analytical models proposed. It has been observed that overall reliability of multi-hop link is improved, with reduction in end-to- end delay is reduced even at lower wakeup rates of a cluster.
IEEE WF-IoT Session: Peer-to-Peer Signal Strength Characteristic Between IoT Devices for Distance Estimation
JoonYoung Jung, ETRI, Korea; Dong-oh Kang, ETRI, Korea; Chang Seok Bae, ETRI, Korea
The Received Signal Strength Indication (RSSI) value of Bluetooth can be used to estimate distance between Internet of Things (IoT) devices. The characteristic of Bluetooth RSSI value is different as environments. IoT devices, within Wireless Body Area Network (WBAN) area, can recognize each other in office environment automatically. Peer to peer distance estimation using the RSSI of Bluetooth is difficult because of large deviation of RSSI value. This paper provides the experimental results of RSSI measurement between IoT devices in office environment. And it applies the Low Pass Filter (LPF) to reduce the deviation of RSSI value. So, we can estimate distance using Bluetooth RSSI LPF data whether the IoT device is within WBAN area or not.
IEEE WF-IoT Session: An Empirical Path Loss Model for Wireless Sensor Network Deployment in a Sand Terrain Environment
Abdulaziz Alsayyar, (Florida Institute of Technology, USA; Ivica N. Kostanic, Florida Institute of Technology, USA; Carlos Otero, Florida Institute of Technology, USA; Mohammed Almeer, Florida Institute of Technology, USA; Kusay Rukieh, Florida Institute of Technology, USA
This session presents a WSN model for predicting signal propagation in terrains characterized by sandy surfaces. To create the model, RF measurements were collected through wireless sensor nodes deployed in a sand terrain environment. From the actual measurements, the parameters of the log-normal shadowing model are fine-tuned to develop an accurate path loss model of WSN deployment in sand terrain environments. In addition, the presented RF measurements and empirical path loss model are compared with measurements and models obtained from long-grass and sparse-tree environments, which were presented in a previous work. The results from the comparison of such different terrains show differences in path loss and empirical models' parameters. Such dissimilarity is due to the differences that exist in the wireless channel of each environment. This observation reveals the significance of the in-field studies and the examination of RF propagation for various WSN potential outdoor deployment scenarios. Furthermore, the proposed model is also compared with Free Space Path Loss (FSPL) and Two-Ray models to demonstrate the inaccuracy of these theoretical models in predicting path loss between wireless sensor nodes deployed in a sand terrain environment.
IEEE WF-IoT Session: A Cost Effective and Sustainable Relief Material Supply Visibility System for Devastated Areas
Shigeya Suzuki, Keio University, Japan; Yuki Sato, Keio University, Japan; Takehiro Yokoishi, Keio University, Japan; Jin Mitsugi, Keio University, Japan
This session explores a cost effective and sustainable relief material visibility system. In an evacuation site such as the one prepared on a disastrous event such as the Tohoku earthquake, we have observed three issues on relief goods supply management: discrepancy between demands and supplies, difficulty of sorting and picking of relief material, and storage strategy to maintain optimal capacity and delivery time. To ease these issues, we developed a system, which supports fulfillment by product category. Also, we implemented the system as a "evacuee support mode" of a traceability system to share both software and hardware assets. By deploying as a dual-mode system, the system can be cost-effective and sustainable. We have developed a prototype system alongside with an agricultural e-commerce system with traceability support. We experimented the prototype at a disaster drill session to see effectiveness of the design.
IEEE WF-IoT Session: Study on the Reduction Effect of Traffic Accident by Using Analysis of Internet Survey
Masahiro Miyaji, Aichi Prefectural University & InfoTOYOTA, LTD, Japan
Traffic fatalities in Japan have declined for twelve years by the comprehensive counter-measure. The efforts include enhancement of vehicle safety performance in passive and preventive safety area. As to passive safety, major reduction effect was brought by airbag system, seat belt and crashworthiness of vehicle. For further reduction of the traffic accident, preventive safety may play more important role. Recently driver's psychosomatic state adaptive driving support system has been highlighted to reduce the traffic accident. For that reason reduction effect of psychosomatic adaptive safety function should be clarified to foster its penetration into the market. Statistical analysis of the traffic incident is highly expected to evaluate reduction effect of the traffic accident of psychosomatic adaptive safety function. To execute the challenge, this study introduced Internet survey by delivering questionnaires to respondents. From the analysis of collected answer, major psychosomatic state of driver is hasty and distraction. As a first step this study focused driver's distraction, which may cause traffic accidents. By using pattern recognition, the detection accuracy of driver's distraction was acquired. The reduction effect of the driver's distraction in the traffic accident was estimated by referring the reduction rate of both ASV (Advanced Safety Vehicle) and Intelligent Transportation Systems.
IEEE WF-IoT Session: Controlling Electric Vehicle Charging in the Smart Grid
Thomas Kunz, Carleton University, Canada; Wang Xiang, Carleton University, Canada; Marc St-Hilaire, Carleton University, Canada
Efficient scheduling and coordination algorithms controlling Electric Vehicle (EV) charging operations can potentially lead to energy consumption reduction and/or load balancing, in conjunction with different electricity pricing methods used in smart grid programs. In order to easily implement different algorithms and evaluate and compare their efficiency against other ideas, a flexible simulation framework is proposed. This simulation framework focuses on demand-side residential energy consumption coordination in response to different pricing methods. It is equipped with an appliance consumption library using realistic values to closely represent the average usage of different types of appliances including EVs. In this paper, a prototype program is developed and used to analyze EV charging and coordination algorithm impacts. The simulation run from the program gives a complete picture of the households' power consumption profile. Some results, analysis, and implications are presented in this paper demonstrating how the proposed tool can be used to study the impact of policy decisions.
IEEE WF-IoT Session: Developing a NovaGenesis Architecture Model for Service Oriented Future Internet and IoT
Antonio M Alberti, National Institute of Telecommunications, Brazil; Dhananjay Singh, Hankuk University of Foreign Studies, Korea
We are designing a NovaGenesis Architecture Model to support Future Internet services, which are going to address some fundamental issues of the Internet of Things, such as address resolution, mobility, routing, scalability, security, and network control. The aim is to support trillion of things connect to the Internet. In NovaGenesis, we have presented a set of distributed systems where any information processing is seen as service. Services organize themselves based on names and agreements to meet semantics rich goals, policies, regulations, etc. Even networking functionalities are considered as services. Every existence could have one or more names: natural language names or self-certifying names. All the communication, processing, and storage are name-oriented. The protocol stacks are built on-demand in a contract-based way. Hence, we can state that Nova-Genesis architecture could be an alternative solution for cur-rent internet-oriented innovations in a scalable manner. The aim of this architecture is the coverage of Internet and sensors oriented smart objects. The paper discusses the proposed model in the context of an Advanced Rural Transportation System.
IEEE WF-IoT TUTORIAL: Application Architectures for Internet of Things State of the Art Research Challenges
Roch Glitho, PhD, Associate Professor and Canada Research Chair, Concordia University, Canada
IEEE WF-IoT Session: Cardea Cloud Based Employee Health and Wellness, An Integrated Wellness Application
Elizabeth Lingg, Oracle, USA; Garrett Leone, Oracle, USA; Kent Spaulding, Oracle, USA; Reza B'Far, Oracle, USA
This session discusses an experimental integrated wellness application that syncs with a wearable device and with a human capital management database to provide a full picture of health and wellness. Wellness is measured at the individual level as well as at the group level. This application uses domain specific algorithms, which are based on scientific research and analysis of biometric data. We investigate the effect of this application on user behavior and wellness habits. We also look for correlations between companies' policies, culture, management practices, and wellness.
IEEE WF-IoT Session: When Devices Become Collaborative Supporting Device Interoperability and Behavior Reconfiguration Across Emergency Management Scenario
Mihaela Brut, Theresis, Thales Services S.A., France; Patrick Gatellier, Theresis, Thales Services S.A., France; Ismail Salhi, Université Paris-Est, France; Sylvain Cherrier, Université Paris-Est, France; Yacine Ghamri-Doudane, University of la Rochelle, France; David Excoffier, Sogeti High Tech, France; Nicolas Dumont, Thales Communications and Security, France; Mario Lopez Ramos, Thales Communications and Security, France
Emergency management is a highly critical domain where the information transmission in real-time to the appropriate stakeholders is essential. Based on the results of the "Web of Objects" ITEA 2 project, this paper presents an IoT-based devices collaboration solution across an emergency management workflow, where the exchanged messages are semantically enriched. This solution includes innovative strategies for addressing the three involved issues: ensuring the device management into an interoperable manner and based on a suitable distributed architecture; setting up different workflows for device collaboration while ensuring their autonomy; establishing a suitable format for exchanged data between devices.
IEEE WF-IoT Session: Adaptive Rule Engine Based on IoT Enabled Remote Health Care Data Acquisition and Smart Transmission System
Malyala Pavana Ravi Sai Kiran, IIT Hyderabad, India; Pachamuthu Rajalakshmi, Indian Institute of Technology Hyderabad, India; Krishna Bharadwaj, IIT Hyderabad, India; Amit Pachamuthu Rajalakshmi, Assistant Professor (Indian Institute of Technology Hyderabad, India)
In the remote health care monitoring applications, the collected medical data from bio-medical sensors should be transmitted to the nearest gateway for further processing. Transmission of data contributes to a significant amount of power consumption by the transmitter and increase in the network traffic. In this paper we propose a low complex rule engine based health care data acquisition and smart transmission system architecture, which uses IEEE 802.15.4 standard for transferring data to the gateway. The power consumed and the network traffic generated by the device can be reduced by event based transmission rather than continuous transmission of data. We developed two different rule engines: static rule engine and adaptive rule engine, which decides whether to transmit the collected data based on the important features extracted from the data, thereby achieving power saving. In this paper, ECG data acquisition and transmission architecture is considered. The metrics used for performance analysis are the amount of power saving and reduction in network traffic. It is shown that the proposed rule engine gives a significant reduction in energy consumption and network traffic generated.
IEEE WF-IoT Session: Modular Framework for Cost Optimization in Smart Grid
Thomas Kunz (Carleton University, Canada; Muhammad Raisul Alam, Carleton University, Canada; Marc St-Hilaire, Carleton University, Canada
A smart power grid transforms the traditional electric grid into a user centric, intelligent power network. This paper addresses the cost optimization problem in the smart grid from the users' perspective. A homeowner can install diverse energy generators and storage devices to reduce the dependency on external energy sources. The widespread utilization of green energy sources creates uncertainty in energy generation due to their unpredictable nature. A user can collaborate with the neighbors to participate in energy trading. The utility indirectly controls the energy consumption and generation in the system by utilizing a demand-oriented time varying price signal. The relationships between the participating components represent a complex unified system because of uncertain energy consumption and power generation disruption. Computational intelligence plays an essential role to coordinate the participating components. This paper proposes a cost optimization framework that breaks the dependencies between the components. The framework transforms the complex unified model into a simpler modular framework. Each module can be solved using different optimization approach, which implies a simple, flexible and traceable strategy for practical implementation.
IEEE WF-IoT Session: Design and Implementation of Vehicle Tracking System Using GPS/GSM/GPRS Technology and Smartphone Application
Girma Tewolde, Kettering University, USA; SeokJu Lee, Kettering University, USA; Jaerock Kwon, Kettering University, USA
An efficient vehicle tracking system is designed and implemented for tracking the movement of any equipped vehicle from any location at any time. The system makes good use of a popular technology that combines a Smartphone application and a microcontroller. This will be inexpensive solution compared to others. The designed in-vehicle device works using GPS/GSM/GPRS technology that is one of the most common ways for vehicle tracking. The device is embedded inside a vehicle whose position is to be tracked in real-time. A microcontroller is used to control the GPS and GSM/GPRS modules. The vehicle tracking system uses the GPS to get geographic coordinates while the GSM/GPRS module is used to transmit and update the vehicle location to a database. A Smartphone application is used for continuously monitoring the vehicle location. The Google Maps API is used to display the vehicle on the map in the Smartphone application. Users will be able to continuously monitor a moving vehicle on demand from their Smartphone and can determine the estimated distance and time for the vehicle to arrive at a given destination. This paper demonstrates the feasibility and effectiveness of the system using successful experimental results.
IEEE WF-IoT Session: Horizontal M2M Platforms Boost Vertical Industry: Effectiveness Study for Building Energy Management Systems
JaeSeung Song, Sejong University, NEC Europe; Martin Flaeck, Apostolos Papageorgiou, Anett Schuelke, NEC Europe
Case studies providing lessons learned and best practices on IoT or M2M projects – Campus21 – energy saving in a building system. Looks at standards and interoperability platforms.
IEEE WF-IoT Session: Design and Implementation of a WiFi Sensor Device Management System
Miika Komu, Ericsson Research
A presentation on WiFi-based sensors and how to manage them.
IEEE WF-IoT Session: An Online Sequential Extreme Learning Machine Approach to WiFi Based Indoor Positioning
Han Zou, EXQUISITUS, Centre for E-City, School of Electrical and Electronics Engineering, Nanyang Technologic & Berkeley Education Alliance for Research in Singapore Limited, Singapore; Hao Jiang, Nanyang Technological University, Singapore; Xiaoxuan Lu, Nanyang Technological University, Singapore; Lihua Xie, University of Nanyang Technological University, Singapore
Developing Indoor Positioning System (IPS) has become an attractive research topic due to the increasing demands on Location Based Service (LBS) in indoor environment recently. WiFi technology has been studied and explored to provide indoor positioning service for years since existing WiFi infrastructures in indoor environment can be used to greatly reduce the deployment costs. A large body of WiFi based IPSs adopt the fingerprinting approach as the localization algorithm. However, these WiFi based IPSs suffer from two major problems: the intensive costs on manpower and time for offline site survey and the inflexibility to environmental dynamics. In this paper, we propose an indoor localization algorithm based on online sequential extreme learning machine (OS-ELM) to address these problems accordingly. The fast learning speed of OS-ELM can reduce the time and manpower costs for the offline site survey, and more importantly, its online sequential learning ability enables the proposed localization algorithm to automatically and timely adapt to the environmental dynamics. The experimental results show that the proposed localization algorithm can provide higher localization accuracy than traditional approaches due to its fast adaptation to various environmental changes.
IEEE WF-IoT Keynote: SK Telecom’s IoT Biz and R&D - Realizing a Smarter World
Alex Jinsung Choi, Ph.D., EVP and Head of ICT R&D, SK Telecom
Addressing the importance of the Internet of Things (IoT), how serious SK Telecom is about IoT, and why other global MNOs (Managed Network Operators), service providers and fixed operators are developing strategies for it. The sky is the only limit for IoT applications and services, which currently include remote maintenance and control, automotive railway, metering, security, retail payments, healthcare and so much more. Industry-wise collaboration and convergence of overall technologies are key to making IoT successful – no one single company can solve or provide the right IoT solutions, so it’s critically important for industry to come together, including open innovation and implementing global standards.