A Disembarking Notification Application for Public Transportation Using Inaudible Frequency

Currently, many people enjoy videos and music content through their smart devices while using public transportation. However, because passengers focus so much on content on their smart devices, they sometimes forget to disembark and miss their destination stations. Therefore, in this paper, we propose an application that can notify users via smart devices when they approach the drop-off point in public transportation using an inaudible high frequency. Inaudible frequency signals are generated with announcements from speakers installed on subways and city buses. Smart devices receive and analyze the signals through their built-in microphones and notify users when they reach the drop-off point. We tested destination notifications with the proposed system and 10 smart devices to evaluate its performance. According to the test results, the proposed system showed 99.4% accuracy on subways and 99.2% accuracy on city buses. Moreover, we compared these results to those using only subway app in subways, and our proposed system achieved far better outcomes. Thus, the proposed system could be a useful technology for notifying smart device users when to get off public transport, and it will become an innovative technology for global public transportation by informing users of their desired stations using speakers.

An Effectiveness and Cost-Estimation Model for Deploying Assistive Technology Solutions in Elderly Care

Background Deployment of modern assistive technologies is one of the major trends contained in the strategies of developed countries. However, the use of technology in households is not yet a common practice. The aim of this paper is present a model for assessment of selected smart device solutions in elderly care and the evaluation of overall care costs. The model provides the optimal set of devices for different target groups in terms of financial savings. Methods The model uses demographic projections taken from Eurostat for EU countries and the disability incidence from the annual report of the Ministry of Labour and Social Affairs of the Czech Republic as an input. The model was implemented in the software Stella Professional dedicated to system dynamics modelling including a web interface and is accessible online. Results In relation to the combination of five assistive devices for the elderly, the optimal solution, the cost savings are 37.8% or182 billion CZK), cumulatively in the simulated time period 2021-2060. Out of the five available assistive devices, up to three - UpWalker, Jaco robotic arm and Poseidon - were employed by the model for different target groups. Conclusion According to the performed analysis the assistive technologies proved a significant potential to maintain the quality of life of elderly and lessen the burden on public budgets. With respect to the ongoing demographic transition, the need to employ smart device solutions should further increase and their price could decline with increasing scale of production and overall advancement in technology.

Crafting Strategies of Security Breaches

In recent years, the number of financial technology players and users have increased at a significant rate due to the rapid technological advancement in financial technology. While smart devices are providing more useful features to users, they have also made it possible for cyber threats to migrate from desktops to smart devices. Thus, it is important for smart device users to be aware that their device could be exposed to cyber threats and that users could protect their devices by employing data-centric cyber security measures. This study reveals how financial technology business model responded to the breach phenomenon by employing data-centric protection approaches. The result is very interesting. Data-centric security is very needed as it is capable of protecting data as a whole. It provides a gapless protection, meaning to say, the data are encrypted and classified wherever it moves. With persistent protection and cross-platform operability, data-centric security will eliminate gaps and keep data protected.

Smart solution for reducing COVID-19 risk using internet of things

The article exposes a smart device designed for mitigating the coronavirus disease (COVID-19) risk using the internet of things. A portable smart alerting device is designed for ensuring safety in public places which can alert people when the guidelines given by the government were not followed and alert health authorities when any abnormalities found. By doing so, the spread of this fatal disease can be stopped. The modules of the proposed system include the face mask detection module, social distance alerting module, crowd detection and analysis module, health screening module and health assessment module. The proposed system can be placed in any public entrances to monitor people without human intervention. Firstly, the human face images are captured for face mask check, then the crowd analysis of the particular entrance where the person is entering is performed, thereafter health screening of the person is done and the values were imported to the health assessment module to check for any abnormalities. Finally, after all the conditions were met the door is opened automatically. The smart device can be installed and effectively used in many scenarios such as malls, stores, crowded places and campuses to avoid the risk of spread of the coronavirus.

Generating Device Fingerprints for Smart Device Pairing Using the Unique Spectrum Characteristic From LEDs

Currently, the vast majority of smart devices with LEDs are on the rise. It has been observed that the lights emitted by each LED have unique spectral characteristics. Despite the fact that there are a number of methods out there to generate fingerprints, none seem to explore the possibility of generating fingerprints using this unique feature. In this chapter, the method to perform device fingerprinting using the unique spectrum emitted from the LED lights is discussed. The generated fingerprint is then used in device pairing.

Autonomous Smart Device for COVID-19 Detection Using Artificial Intelligence

Corona is a pandemic disease and is spreading all over the world. There is also lack of corona virus detection machines. If it is detected at very early stages without pathological intervention, then further spreading of the disease can be controlled, and many of human lives can be saved. So, the proposed biomedical device can be used for fast and accurate prediction of COVID-19 from chest x-rays. X-ray can also be taken from anywhere and sent through any communication medium. Even if error is added, it can be removed using error concealment algorithms. Automated AI-based systems will be used for prediction of normal, COVID-19, and pneumonic cases from x-ray images. It makes detection of COVID-19 infection less costly and portable. This device can be stored in less stringent conditions, making it more effective.