Contact-free Interaction with Mobile Devices using Magnetic, Lighting and Infrared Sources

In the area of Human-Computer Interaction (HCI), the concept of Around Device Interaction (ADI) is gaining special attention nowadays. It provides the possibility of interacting with the device by making use of gestures made in the surrounding space, as well as by detecting certain ambient changes, thus eliminating the need of direct physical contact. Contact-free interaction can be useful for wearable and smart devices, especially in cases where operating with small buttons and touchscreens appears to be particularly inconvenient. This paper presents alternative techniques for smartphone interaction based on different sensory inputs. Namely, external sources of magnetic field, light, and infrared (IR) signals are used to manipulate device sensors' readings which are in turn interpreted as the corresponding interaction commands. Proof-of-concept mobile applications are developed and here presented, demonstrating both the potentials and utility of the contact-free interaction. Specifically, small neodymium magnet was used for smartphone text entry, typical battery flashlight served for sending information to device via Morse code, as well as for alarm triggering, and voice-enabled control device was utilized for invoking smartphone calls from a distance. The presented interaction techniques do not require smartphone hardware alterations. While the usage of built-in magnetic field and ambient light sensors is assumed, peripheral infrared receiver can be used in order to provide IR-based support.

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MAGNETIC FIELD IMPACT UPON TRIBOTECHNICAL CHARACTERISTICS OF PERMANENT CONNECTIONS IN RELATION TO FRICTION SHOCK ABSORBERS

Bulletin of Bryansk state technical university ◽

10.30987/1999-8775-2020-10-4-11 ◽

2020 ◽

Vol 2020 (10) ◽

pp. 4-11

Author(s):

Victor Tikhomirov ◽

Aleksandr Gorlenko ◽

Stanislav Volohov ◽

Mikhail Izmerov

Keyword(s):

Magnetic Field ◽

Friction Factor ◽

Physical Contact ◽

Active Centers ◽

Press Fit ◽

Electro Magnetic Field ◽

Investigation Methods ◽

Electro Magnetic ◽

The Impact ◽

The Magnetic Field

The work purpose is the investigation of magnetic field impact upon properties of friction steel surfaces at fit stripping with tightness through manifested effects and their wear visually observed. On the spots of a real contact the magnetic field increases active centers, their amount and saturation with the time of dislocation outlet, and has an influence upon tribo-mating. The external electro-magnetic field promotes the increase of the number of active centers at the expense of dislocations outlet on the contact surface, and the increase of a physical contact area results in friction tie strengthening and growth of a friction factor. By the example of friction pairs of a spentonly unit in the suspension of coach cars there is given a substantiation of actuality and possibility for the creation of technical devices with the controlled factor of friction and the stability of effects achieved is also confirmed experimentally. Investigation methods: the fulfillment of laboratory physical experiments on the laboratory plant developed and patented on bush-rod samples inserted with the fit and tightness. The results of investigations and novelty: the impact of the magnetic field upon the value of a stripping force of a press fit with the guaranteed tightness is defined. Conclusion: there is a possibility to control a friction factor through the magnetic field impact upon a friction contact.

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Augmenting Around-Device Interaction by Geomagnetic Field Built-in Sensor Utilization

Sensors ◽

10.3390/s21093087 ◽

2021 ◽

Vol 21 (9) ◽

pp. 3087

Author(s):

Sandi Ljubic ◽

Franko Hržić ◽

Alen Salkanovic ◽

Ivan Štajduhar

Keyword(s):

Magnetic Field ◽

Neural Networks ◽

Curve Fitting ◽

Absolute Error ◽

Interaction Space ◽

Text Entry ◽

Proof Of Concept ◽

Field Sensor ◽

Device Interaction ◽

Input Techniques

In this paper, we investigate the possibilities for augmenting interaction around the mobile device, with the aim of enabling input techniques that do not rely on typical touch-based gestures. The presented research focuses on utilizing a built-in magnetic field sensor, whose readouts are intentionally affected by moving a strong permanent magnet around a smartphone device. Different approaches for supporting magnet-based Around-Device Interaction are applied, including magnetic field fingerprinting, curve-fitting modeling, and machine learning. We implemented the corresponding proof-of-concept applications that incorporate magnet-based interaction. Namely, text entry is achieved by discrete positioning of the magnet within a keyboard mockup, and free-move pointing is enabled by monitoring the magnet’s continuous movement in real-time. The related solutions successfully expand both the interaction language and the interaction space in front of the device without altering its hardware or involving sophisticated peripherals. A controlled experiment was conducted to evaluate the provided text entry method initially. The obtained results were promising (text entry speed of nine words per minute) and served as a motivation for implementing new interaction modalities. The use of neural networks has shown to be a better approach than curve fitting to support free-move pointing. We demonstrate how neural networks with a very small number of input parameters can be used to provide highly usable pointing with an acceptable level of error (mean absolute error of 3 mm for pointer position on the smartphone display).

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Robust voice user interface for internet-of-things

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-201781 ◽

2021 ◽

pp. 1-16

Author(s):

Abdelaziz A. Abdelhamid ◽

Sultan R. Alotaibi

Keyword(s):

Internet Of Things ◽

Smart Home ◽

Industrial Revolution ◽

Rapid Development ◽

Smart Devices ◽

Voice User ◽

Voice Interaction ◽

Device Interaction ◽

Computational Resources ◽

Human Device

Internet of things (IoT) plays significant role in the fourth industrial revolution and attracts an increasing interest due to the rapid development of smart devices. IoT comprises factors of twofold. Firstly, a set of things (i.e., appliances, devices, vehicles, etc.) connected together via network. Secondly, human-device interaction to communicate with these things. Speech is the most natural methodology of interaction that can enrich user experience. In this paper, we propose a novel and effective approach for building customized voice interaction for controlling smart devices in IoT environments (i.e., Smart home). The proposed approach is based on extracting customized tiny decoding graph from a large graph constructed using weighted finite sates transducers. Experimental results showed that tiny decoding graphs are very efficient in terms of computational resources and recognition accuracy in clean and noisy conditions. To emphasize the effectiveness of the proposed approach, the standard Resources Management (RM1) dataset was employed and promising results were achieved when compared with four competitive approaches.

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Research on Human-Computer Interaction Control Method in the Background of Internet of Things

Journal of Interconnection Networks ◽

10.1142/s0219265921430155 ◽

2021 ◽

Author(s):

Yingying Hu ◽

Zhongyang Li

Keyword(s):

Internet Of Things ◽

Control Method ◽

Computer Control ◽

Control Device ◽

Smart Devices ◽

The Internet ◽

Interactive Control ◽

Interaction Control ◽

Different Types ◽

The Internet Of Things

Against the background of the growing development of the Internet of Things, this article conducts research on more efficient methods for controlling the interconnection of all things, and proposes that smart devices use the same operating platform, and the human-computer interface presents universal modular controls for manipulation, it can satisfy the requirement that one device controls several different types of controlled device simultaneously. At the same time, the interactive method uses the controlled device to actively submit control content to the control device, and discusses the human-computer interactive control method applicable to the Internet of Everything, and strives to achieve a convenient and easy-to-use human-computer control experience.

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Fluorescent magnetosomes for controlled and repetitive drug release under the application of an alternating magnetic field under conditions of limited temperature increase (<2.5 °C)

Nanoscale ◽

10.1039/c8nr02164c ◽

2018 ◽

Vol 10 (23) ◽

pp. 10918-10933 ◽

Cited By ~ 8

Author(s):

Edouard Alphandéry ◽

Darine Abi Haidar ◽

Olivier Seksek ◽

François Guyot ◽

Imène Chebbi

Keyword(s):

Magnetic Field ◽

Antitumor Activity ◽

Drug Release ◽

Temperature Increase ◽

Alternating Magnetic Field ◽

Limited Temperature ◽

External Sources

Therapeutic substances bound to nanoparticles have been shown to dissociate following excitation by various external sources of energies or chemical disturbance, resulting in controllable and efficient antitumor activity.

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Pervasive computing in the context of COVID-19 prediction with AI-based algorithms

International Journal of Pervasive Computing and Communications ◽

10.1108/ijpcc-07-2020-0082 ◽

2020 ◽

Vol 16 (5) ◽

pp. 477-487 ◽

Cited By ~ 3

Author(s):

Magesh S. ◽

Niveditha V.R. ◽

Rajakumar P.S. ◽

Radha RamMohan S. ◽

Natrayan L.

Keyword(s):

Machine Learning ◽

Mathematical Model ◽

Pervasive Computing ◽

Research Work ◽

Previous History ◽

Physical Contact ◽

Machine Learning Techniques ◽

Smart Devices ◽

Susceptible Population ◽

Content Type

Purpose The current and on-going coronavirus (COVID-19) has disrupted many human lives all over the world and seems very difficult to confront this global crisis as the infection is transmitted by physical contact. As no vaccine or medical treatment made available till date, the only solution is to detect the COVID-19 cases, block the transmission, isolate the infected and protect the susceptible population. In this scenario, the pervasive computing becomes essential, as it is environment-centric and data acquisition via smart devices provides better way for analysing diseases with various parameters. Design/methodology/approach For data collection, Infrared Thermometer, Hikvision’s Thermographic Camera and Acoustic device are deployed. Data-imputation is carried out by principal component analysis. A mathematical model susceptible, infected and recovered (SIR) is implemented for classifying COVID-19 cases. The recurrent neural network (RNN) with long-term short memory is enacted to predict the COVID-19 disease. Findings Machine learning models are very efficient in predicting diseases. In the proposed research work, besides contribution of smart devices, Artificial Intelligence detector is deployed to reduce false alarms. A mathematical model SIR is integrated with machine learning techniques for better classification. Implementation of RNN with Long Short Term Memory (LSTM) model furnishes better prediction holding the previous history. Originality/value The proposed research collected COVID −19 data using three types of sensors for temperature sensing and detecting the respiratory rate. After pre-processing, 300 instances are taken for experimental results considering the demographic features: Sex, Patient Age, Temperature, Finding and Clinical Trials. Classification is performed using SIR mode and finally predicted 188 confirmed cases using RNN with LSTM model.

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A Magnetic Field Sensor Array as an Universal Smart Home Control Device

2019 IEEE 8th Global Conference on Consumer Electronics (GCCE) ◽

10.1109/gcce46687.2019.9015374 ◽

2019 ◽

Author(s):

Phil Meier ◽

Kris Rohrmann ◽

Oussama Ferhi ◽

Marvin Sandner ◽

Marcus Prochaska

Keyword(s):

Magnetic Field ◽

Smart Home ◽

Sensor Array ◽

Control Device ◽

Magnetic Field Sensor ◽

Field Sensor

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Effect of electric and magnetic fields on operation of insulin pumps under 400 kV power lines

Radioprotection ◽

10.1051/radiopro/2019047 ◽

2020 ◽

Vol 55 (1) ◽

pp. 51-54

Author(s):

L. Korpinen ◽

R. Pääkkönen ◽

M. Penttilä

Keyword(s):

Magnetic Field ◽

Remote Control ◽

Insulin Pump ◽

Test Site ◽

Control Device ◽

Power Lines ◽

Insulin Pumps ◽

Electric And Magnetic Fields ◽

Before And After ◽

The Magnetic Field

The aim was to study the operation of insulin pumps under a 400 kV transmission line (two test places) and possible disturbances that the lines could have caused. Three different insulin pumps were attached one at a time to the subject’s clothes. The diabetes nurse started the pumps before the tests to ensure the correct settings were being utilized. After walking under the power lines when meters were running, she tested if the meters had operated properly. At the first test site (A), the electric field was 5.0–5.1 kV/m and the magnetic field 8.6–10.9 μT, and in the second test place (B), the fields were 7.7–8.5 kV/m and 5.7–9.2 μT. The pumps worked perfectly: no disruption was detected in the flow, display or menu movement, and the events were registered correctly. Only the remote control, which worked well before and after the test, could not reliably receive additional doses. However, the functions of the insulin pump are not dependent on the functionality of the remote control device, so the study suggests that insulin pump users can move safely under the power lines.

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