Machine To Machine
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Energy conversion and conditioning technologies, power electronics, adjustable speed drives and their applications, power electronics for smarter grid, energy efficiency,technologies for sustainable energy systems, converters and power supplies
ISIE focuses on advancements in knowledge, new methods, and technologies relevant to industrial electronics, along with their applications and future developments.
All topics related to engineering and technology management, including applicable analytical methods and economical/social/human issues to be considered in making engineering decisions.
The scope of the 2020 IEEE/ASME AIM includes the following topics: Actuators, Automotive Systems, Bioengineering, Data Storage Systems, Electronic Packaging, Fault Diagnosis, Human-Machine Interfaces, Industry Applications, Information Technology, Intelligent Systems, Machine Vision, Manufacturing, Micro-Electro-Mechanical Systems, Micro/Nano Technology, Modeling and Design, System Identification and Adaptive Control, Motion Control, Vibration and Noise Control, Neural and Fuzzy Control, Opto-Electronic Systems, Optomechatronics, Prototyping, Real-Time and Hardware-in-the-Loop Simulation, Robotics, Sensors, System Integration, Transportation Systems, Smart Materials and Structures, Energy Harvesting and other frontier fields.
IECON is focusing on industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.
Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission
Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...
2018 XIV International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE), 2018
This paper defines the problem and offers solutions to calibrate the location estimation in the Machine-to-Machine (M2M) system to a given scale set out in the customer specifications. The authors developed the classification of subscriber location tasks depending on practical application. The choice of tasks is process-based and proceeds without human participation. The solutions of such problems are in demand ...
2017 IEEE Symposium on Computers and Communications (ISCC), 2017
Machine-to-machine communication (M2M) is a core elements in the Internet of Things (IoT) vision. Due to the large number of devices expected, the Long- term Evolution-Advanced (LTA-A) networks may present congestion and overload problems. In this paper, we present two approaches to mitigate the impact of M2M communication in LTE-A. We model such overloaded scenario as a bankruptcy problem and ...
2018 International Conference on Information and Communication Technology Convergence (ICTC), 2018
Machine-to-Machine (M2M) Communication is becoming one of the emerging paradigms to enable a broad range of applications from the massive deployment of sensor devices to mission-critical services. Nevertheless, having a massive number of M2M devices activated simultaneously is difficult to tackle and it can cause some issues in connection establishment that leads to degrading the network performance. In order to ...
2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS), 2016
Obesity/overweight patient is a person who has excessive body weight which prone to have serious diseases like heart disease, stroke, diabetes, some types of cancer, and osteoarthritis. In general, obesity/overweight is caused by some factors: excessive food intake, lack of physical activities, and genetics. In 2013, more than 2 billion people suffer obesity/overweight including 40 million in Indonesia. To overcome ...
2017 International Workshop on Antenna Technology: Small Antennas, Innovative Structures, and Applications (iWAT), 2017
Machine-to-Machine (M2M) networks have recently drawn significant attention as a result of the vast number of potential applications associated with them; however, consensus on the use of a standardized air interface protocol has not been reached yet. Due to their nature, M2M radio networks are expected to be densely populated and therefore prone to Multiple Access interference (MAI); in this ...
Welcome Remarks - Doug Zuckerman: 2016 Technology Time Machine
Brain Panel Introduction - Paul Sadja: 2016 Technology Time Machine
Big Data Panelist - Ritu Chadha: 2016 Technology Time Machine
Cat and Mouse, Email Phishing and Machine Learning - Cybersecurity in a Hyperconnected World
EMBC 2011-Panel Discussion-Frontiers and Future Trends in Brain-Machine Interface
Machine Learning of Motor Skills for Robotics
Women Making the Future Panelist - Kathy Herring Hyashi: 2016 Technology Time Machine
Machine Ethics - Proceedings of the IEEE Webinar
IEEE 125th Anniversary Media Event: Brain-Machine Interface Technology
Multimodal Telepresent Control of DLR Rollin' JUSTIN
Hardware-Software Co-Design for an Analog-Digital Accelerator for Machine Learning - Dejan Milojicic - ICRC 2018
IEEE Day Future Milestone: Machine Learning in the future
Brain Panelist - Jan Rabaey: 2016 Technology Time Machine
Shannon to Machine Learning: ML & DL for 5G - Erik Stauffer - B5GS 2019
Signal Processing and Machine Learning
Panel Q&A - Big Data: 2016 Technology Time Machine
Keynote - AT&T's Alicia Abella: 2016 Technology Time Machine
Internet of Things Panelist - Antonio Skarmeta: 2016 Technology Time Machine
Q&A with Mary Ward-Callan: IEEE Technology Time Machine Podcast, Episode 1
This paper defines the problem and offers solutions to calibrate the location estimation in the Machine-to-Machine (M2M) system to a given scale set out in the customer specifications. The authors developed the classification of subscriber location tasks depending on practical application. The choice of tasks is process-based and proceeds without human participation. The solutions of such problems are in demand within the smart city paradigm.
Machine-to-machine communication (M2M) is a core elements in the Internet of Things (IoT) vision. Due to the large number of devices expected, the Long- term Evolution-Advanced (LTA-A) networks may present congestion and overload problems. In this paper, we present two approaches to mitigate the impact of M2M communication in LTE-A. We model such overloaded scenario as a bankruptcy problem and apply two strategies to define how resources should be allocated. The simulation results show that our approaches present improvements in terms of energy efficiency, impact control of M2M over Human-to-human (H2H) and define priority among different classes of device.
Machine-to-Machine (M2M) Communication is becoming one of the emerging paradigms to enable a broad range of applications from the massive deployment of sensor devices to mission-critical services. Nevertheless, having a massive number of M2M devices activated simultaneously is difficult to tackle and it can cause some issues in connection establishment that leads to degrading the network performance. In order to tackle this issues, we propose a random access management that can optimize the QoS of the M2M-related application. The proposed approach handles the signaling process within a group of related M2M devices, thus preventing unnecessary recurring data transmission, and reusing the assigned PRACH. Results show that our approach significantly improves the network performance in term of the probability of random access and the number of preamble transmission.
Obesity/overweight patient is a person who has excessive body weight which prone to have serious diseases like heart disease, stroke, diabetes, some types of cancer, and osteoarthritis. In general, obesity/overweight is caused by some factors: excessive food intake, lack of physical activities, and genetics. In 2013, more than 2 billion people suffer obesity/overweight including 40 million in Indonesia. To overcome obesity/overweight, patients should control their food intakes and do physical activities. In most cases, the problem is they don't know whether their foods are good or not for their weights, and in the end, they fail to control their weights. This research helps weight loss program with machine-to-machine (M2M) technology with using special weight scale which can upload data to the server. Website and mobile application are built to give recommendation what food to eat today based on calorie calculation, in order to reduce their weight during the program.
Machine-to-Machine (M2M) networks have recently drawn significant attention as a result of the vast number of potential applications associated with them; however, consensus on the use of a standardized air interface protocol has not been reached yet. Due to their nature, M2M radio networks are expected to be densely populated and therefore prone to Multiple Access interference (MAI); in this paper, a radio interference evaluation framework is used to evaluate the performance of Impulse Radio Ultra Wideband (IR-UWB) as physical layer (PHY) for broadband M2M indoor networks. Considering an accurate channel model for the indoor environment, simulated results for the intra-network interference are presented. In order to obtain a realistic perspective of the system performance, different scenarios have been studied and the stochastic nature of both the network topology and the channel traffic have been taken into account. Finally, the use of a simple yet efficient power control scheme is proposed and evaluated yielding interesting results.
In this paper are presented the results regarding the design and the implementation of an enhanced digital transmission system dedicated especially for applications in the field of machine to machine communications. The improved performances of the system, regarding the transmission speed, spectral efficiency and the resistance to noises, are ensured by the very efficient and reliable implementation based on quadrature phase-shift keying (QPSK) modulation technique. For obtaining a bidirectional communication, the architecture of the proposed design relies on a cascaded configuration. For each direction of communication are used pairs of AD 633 multipliers connected in symmetrical structures that forms a set of balanced quadrature modulators and demodulators. The synchronization of the emission and reception modules that compose the system is realized with a custom scheme that use specialized circuits based on phase-locked-loop principle. Compared with other implementations, the proposed transmission system represents a very suitable solution for direct communication and extended data exchange between various devices, including industrial instrumentation and other equipments that can be integrated into larger networks for increased efficiency.
In the coming decades, we will live in a world surrounded by tens of billions of devices that will interoperate and collaborate in an effort to deliver personalized and autonomic services. This paradigm of smart objects and smart things interconnected and ubiquitously surrounding us is called the Internet of Things (IoT). Cities may be the first to benefit from the IoT, but reliance on these machines to make decisions has profound implications for trust, and makes mechanisms for expressing and reasoning about trust essential. This paper introduces the project funded by the Georgia Tech Research Institute to look at several dimensions of Machine to Machine Trust in the context of Smart Cities.
In this paper, a Machine to Machine (M2M) Relay mechanism is proposed to save energy consumption by reducing the number of repetition in a Narrowband Internet of Things (NB-IoT) system, which is a 3rd Generation Partnership Project (3GPP) user equipment (UE) category for low-power, low-complexity and battery-powered devices. A NB-IoT system can support the access of a large number of devices ranging over a coverage area larger than the typical cell in a cellular mobile network by adopting the repetition-based transmission to increase the receiver processing gain, i.e., to increase the chance of successful data transmission. 3GPP NB-IoT RAN1 already defines that the number of repetition will binary exponentially increase when the receiving signal strength decreases. This may induce surplus repetition, i.e., unnecessary energy consumption. Moreover, for devices in the edge of a cell, the inferior radio condition will incur abundant repetitions, depleting the battery energy very quickly. Thus, by using the Machine to Machine (M2M) Relay that is already developed and defined in 3GPP standard, a novel mechanism for adequate relay UE selecting and optimal relay scheduling is proposed to effectively reduce the energy consumption but maintain the system throughput and UE QoS. The extensive simulations is executed in a setting of 1000 devices distributed according to a Poisson Point Process over a cell of the radios of 125 transmission distance units. If a UE located within a transmission distance unit to the eNB; it needs only one repetition to successfully transmit data. Simulation results show that the repetition number will drop dramatically in all simulation cases. The less number of transmitting devices, the higher saving ration of repetition. For transmitting device density 0.1, 0.2, and 0.3, the repetition saving ratio is 0.7, 0.69, and 0.65 respectively. This indicating that by the proposed M2M relay scheduling mechanism, when the transmitting device density is 0.3, the system can save a huge 65% energy consumption.
In the near future, with the development of Machine to Machine (M2M) communication service providers may see a spike in traffic degrading the quality of service (QoS). With the addition of several M2M devices, it is expected to create conditions for overload in the Radio Access Network (RAN) and Core Network in 3GPP LTE networks. There are many studies that examine various characteristics of M2M communication devices including protecting the physical devices, authentication methods, congestion controls, privacy protection and many others. However, congestion will be a persistent problem with the increased devices and is the focus of this paper. There is research on the methods to control congestion, though this paper is considering increasing availability through reducing total bytes transmitted and thus avoiding or reducing overload and congestion in LTE network. In this paper, we have proposed and tested various optimizing mechanisms for reducing the signalling traffic and bandwidth utilization, thus decreasing the overload in the LTE architecture.
It is critical for machines in cognitive radio based machine-to-machine networks to efficiently utilize idle radio bands, efficiently utilize energy and alleviate the radio interference of primary users. In this paper, we propose a dynamic permission probability control for packet reservation multiple access in cognitive radio based machine type communication networks. Using the proposed permission probability control, a machine could take into account the interference of primary users to dynamically adjust the permission probability such that more data can be sent while radio interference is alleviated. Simulation results show that the proposed dynamic permission probability can increase utilization of time slots (or throughput) and efficiency of power usage under the constraint of interference ratio.
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