An Energy-Efficient IoT node for HMI applications based on an ultra-low power Multicore Processor

Kartsch, Victor; Guermandi, Marco; Benatti, Simone; Montagna, Fabio; Benini, Luca

doi:10.1109/sas.2019.8705984

Cited by 17 publications

(8 citation statements)

References 19 publications

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“…Therefore, the energy harvesting efficiency is set at 0.4. The real test in [ 27 ] shows that a smart IoT node processes a pattern recognition with a power of 11.84 mW. Hence, the minimum required harvesting energy here is set at 10 mW.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Simultaneous Wireless Information and Power Transfer in Multi-User OFDMA Networks with Physical Secrecy

Sangmahamad

Woradit

Saengudomlert

2022

Sensors

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This paper considers simultaneous wireless information and power transfer (SWIPT) from a base station to multiple Internet of Things (IoT) nodes via orthogonal frequency-division multiple access (OFDMA), where every node can eavesdrop on the subcarriers allocated to other nodes. Application layer encryption is unsuitable for IoT nodes relying on energy harvesting, and physical layer secrecy should be deployed. The different channels among users on every subcarrier can be exploited to obtain physical layer secrecy without using artificial noise. We propose an algorithm to maximize the secrecy rate of IoT nodes by jointly optimizing the power splitting ratio and subcarrier allocation. For fairness, the lowest total secrecy rate among users is maximized. Through simulations, the proposed algorithm is compared with the minimum effort approach, which allocates each subcarrier to the strongest node and selects the minimum sufficient power splitting ratio. The obtained secrecy rate is 3 times (4.5 over 1.5 bps/Hz) higher than that of the minimum effort approach in every case of parameters: the base station’s transmit power, the minimum harvested energy requirement of an IoT node and the energy harvesting efficiency.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Simultaneous Wireless Information and Power Transfer in Multi-User OFDMA Networks with Physical Secrecy

Sangmahamad

Woradit

Saengudomlert

2022

Sensors

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“…For example, a touch screen and joystick are HMI, a user interface connecting a person to a machine. The global HMI market is expected to generate more than $8 billion in revenue from 2017 to 2023 . Among various HMI fields, the field of healthcare is receiving a lot of attention.…”

Section: Introductionmentioning

confidence: 99%

Soft Wireless Headband Bioelectronics and Electrooculography for Persistent Human–Machine Interfaces

Ban

Lee

Kwon

et al. 2023

ACS Appl. Electron. Mater.

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Recent advances in wearable technologies have enabled ways for people to interact with external devices, known as human−machine interfaces (HMIs). Among them, electrooculography (EOG), measured by wearable devices, is used for eye movement-enabled HMI. Most prior studies have utilized conventional gel electrodes for EOG recording. However, the gel is problematic due to skin irritation, while separate bulky electronics cause motion artifacts. Here, we introduce a low-profile, headband-type, soft wearable electronic system with embedded stretchable electrodes, and a flexible wireless circuit to detect EOG signals for persistent HMIs. The headband with dry electrodes is printed with flexible thermoplastic polyurethane. Nanomembrane electrodes are prepared by thin-film deposition and laser cutting techniques. A set of signal processing data from dry electrodes demonstrate successful real-time classification of eye motions, including blink, up, down, left, and right.Our study shows that the convolutional neural network performs exceptionally well compared to other machine learning methods, showing 98.3% accuracy with six classes: the highest performance till date in EOG classification with only four electrodes. Collectively, the real-time demonstration of continuous wireless control of a two-wheeled radio-controlled car captures the potential of the bioelectronic system and the algorithm for targeting various HMI and virtual reality applications.

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“…IoT security cameras use a low-power processor because they should always be activated [ 10 ]. The low-power processor generally has a lower performance than standard computer processors [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

JLVEA: Lightweight Real-Time Video Stream Encryption Algorithm for Internet of Things

Yun

Kim

2020

Sensors

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Along with the recent growth of Internet of Things (IoT) security camera market, there have been a number of personal information leakage incidents from security attacks targeting such cameras. Therefore, a permutation-based video encryption algorithm was proposed to secure video streams in low-performance processors such as IoT security cameras. However, existing permutation-based video encryption algorithms are vulnerable to known-plaintext attacks since they use the same permutation list for every frame. Moreover, situation deduction based on the color composition is possible. In this paper, we propose a new permutation-based video encryption algorithm that updates the permutation list for every frame using a crypto secure pseudo-random number generator without significantly increasing memory usage. By doing so, the algorithm becomes robust to known-plaintext attacks, which has been a common problem with existing permutation-based video encryption algorithms. In addition, color channel separation can prevent attackers from deducing situations through color composition. Pre-compression encryption is applied to make the algorithm robust to data loss because of packet loss. We implement the proposed algorithm and conduct an experiment to show its performance in terms of probability of data loss because of packet loss, encryption speed, and memory usage.

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An Energy-Efficient IoT node for HMI applications based on an ultra-low power Multicore Processor

Cited by 17 publications

References 19 publications

Simultaneous Wireless Information and Power Transfer in Multi-User OFDMA Networks with Physical Secrecy

Simultaneous Wireless Information and Power Transfer in Multi-User OFDMA Networks with Physical Secrecy

Soft Wireless Headband Bioelectronics and Electrooculography for Persistent Human–Machine Interfaces

JLVEA: Lightweight Real-Time Video Stream Encryption Algorithm for Internet of Things

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