Gesture recognition using mobile phone's inertial sensors

The availability of inertial sensors embedded in mobile devices has enabled a new type of interaction based on the movements or “gestures” made by the users when holding the device. In this paper we propose a gesture recognition system for mobile devices based on accelerometer and gyroscope measurements. The system is capable of recognizing a set of predefined gestures in a user-independent way, without the need of a training phase. Furthermore, it was designed to be executed in real-time in resource-constrained devices, and therefore has a low computational complexity. The performance of the system is evaluated offline using a dataset of gestures, and also online, through some user tests with the system running in a smart phone

A Review of Physical Human Activity Recognition Chain Using Sensors

In the era of Internet of Medical Things (IoMT), healthcare monitoring has gained a vital role nowadays. Moreover, improving lifestyle, encouraging healthy behaviours, and decreasing the chronic diseases are urgently required. However, tracking and monitoring critical cases/conditions of elderly and patients is a great challenge. Healthcare services for those people are crucial in order to achieve high safety consideration. Physical human activity recognition using wearable devices is used to monitor and recognize human activities for elderly and patient. The main aim of this review study is to highlight the human activity recognition chain, which includes, sensing technologies, preprocessing and segmentation, feature extractions methods, and classification techniques. Challenges and future trends are also highlighted.

Research of MEMS accelerometers features in mobile phone

The purpose of this study is exploring the possibilities of MEMS accelerometer of mobile phone Nokia N900 to determine human gait or similar tasks. This study answers the question of whether you can use this sensor to solve these problems. Main emphasis is on accelerometer-based human gait identification. Previous studies proved that human gait contains very distinctive patterns that can be used for identification and verification purposes. There are different approaches for identification of a gait: accelerometers [1], sensors on the floor [2], motion analysis system, image registration. This means that person can be recognized by his walking style using MEMS accelerometers, which modern phones are equipped by

A Behavioral Model System for Implicit Mobile Authentication

Smartphones are increasingly essential to users’ everyday lives. Security concerns of data compromises are growing, and explicit authentication methods are proving to be inconvenient and insufficient. Meanwhile, users demand quicker and more secure authentication. To address this, a user can be authenticated continuously and implicitly, through understanding consistency in their behavior. This research project develops a Behavioral Model System (BMS) that records users’ behavioral metrics on an Android device and sends them to a server to develop a behavioral model for the user. Once a strong model is generated with TensorFlow, a user’s most recent behavior is queried against the model to authenticate them. The model is tested across its metrics to evaluate the reliability of BMS

Algorithms for Constructing Vehicle Trajectories in Urban Networks Using Inertial Sensors Data from Mobile Devices

Vehicle trajectories are an important source of information for estimating traffic flow characteristics. Lately, several studies have focused on identifying a vehicle’s trajectory in traffic network using data from mobile devices. However, these studies predominantly employed GPS coordinate information for tracking a vehicle’s speed and position in the transportation network. Considering the known limitations of GPS, such as, connectivity issues at urban canyons and underpasses, low precision of localization, high power consumption of device while GPS is in use, this research focuses on developing alternate methods for identifying a vehicle’s trajectory at an intersection and at a urban grid network using sensor data other than GPS in order to minimize GPS dependency. In particular, accelerometer and gyroscope data collected using smartphone’s inertial sensors, and speed data collected using an on-board diagnostics (OBD) device, are utilized to develop algorithms for maneuver (i.e., left/right turn and through), trip direction, and trajectory identification. Different algorithms using threshold of gyroscope and magnetometer readings, and machine learning techniques such as k-medoids clustering and dynamic time warping are developed for maneuver identification and their accuracy is tested on collected field data. It is found that, clustering based on maximum and minimum value of gyroscope readings is effective for maneuver identification. For trip direction identification at an intersection, two different methods are developed and tested. The first method utilizes accelerometer, gyroscope and OBD speed data, and the 2nd method employs magnetometer and acceleration data. The results demonstrate that the developed method using accelerometer, gyroscope and OBD speed data are effective in identifying a vehicle’s direction. An effective algorithm is developed using OBD speed information, maneuver and trip direction identification algorithms to identify vehicle’s trajectory at a grid network. Techniques for noise removal and orientation correction to transfer the raw data from phone’s local coordinate to global coordinate system are also demonstrated. Overall, this research eliminates the need for continuous GPS connectivity for trajectory identification. This research can be incorporated in methods developed by researchers to estimate traffic flow, delays, and queue lengths at intersections. This information can lead to better signal timings, travel recommendations, and traffic updates

Accessible options for deaf people in e-Learning platforms: technology solutions for sign language translation

AbstractThis paper presents a study on potential technology solutions for enhancing the communication process for deaf people on e-learning platforms through translation of Sign Language (SL). Considering SL in its global scope as a spatial-visual language not limited to gestures or hand/forearm movement, but also to other non-dexterity markers such as facial expressions, it is necessary to ascertain whether the existing technology solutions can be effective options for the SL integration on e-learning platforms. Thus, we aim to present a list of potential technology options for the recognition, translation and presentation of SL (and potential problems) through the analysis of assistive technologies, methods and techniques, and ultimately to contribute for the development of the state of the art and ensure digital inclusion of the deaf people in e-learning platforms. The analysis show that some interesting technology solutions are under research and development to be available for digital platforms in general, but yet some critical challenges must solved and an effective integration of these technologies in e-learning platforms in particular is still missing

Towards Secure, Power-Efficient and Location-Aware Mobile Computing

In the post-PC era, mobile devices will replace desktops and become the main personal computer for many people. People rely on mobile devices such as smartphones and tablets for everything in their daily lives. A common requirement for mobile computing is wireless communication. It allows mobile devices to fetch remote resources easily. Unfortunately, the increasing demand of the mobility brings many new wireless management challenges such as security, energy-saving and location-awareness. These challenges have already impeded the advancement of mobile systems. In this dissertation we attempt to discover the guidelines of how to mitigate these problems through three general communication patterns in 802.11 wireless networks. We propose a cross-section of a few interesting and important enhancements to manage wireless connectivity. These enhancements provide useful primitives for the design of next-generation mobile systems in the future.;Specifically, we improve the association mechanism for wireless clients to defend against rogue wireless Access Points (APs) in Wireless LANs (WLANs) and vehicular networks. Real-world prototype systems confirm that our scheme can achieve high accuracy to detect even sophisticated rogue APs under various network conditions. We also develop a power-efficient system to reduce the energy consumption for mobile devices working as software-defined APs. Experimental results show that our system allows the Wi-Fi interface to sleep for up to 88% of the total time in several different applications and reduce the system energy by up to 33%. We achieve this while retaining comparable user experiences. Finally, we design a fine-grained scalable group localization algorithm to enable location-aware wireless communication. Our prototype implemented on commercial smartphones proves that our algorithm can quickly locate a group of mobile devices with centimeter-level accuracy

Навігаційна система числення шляху на основі мобільного телефону

Робота публікується згідно наказу ректора від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт вищої освіти в репозиторії університету". Керівник дипломної роботи: д.т.н., проф. кафедри авіаційних комп’ютерно-інтегрованих комплексів, Мухіна Марина ПетрівнаУ сучасному світі, що динамічно розвивається, людина займає провідні позиції, в таких умовах розвивається ринок складних автоматизованих інтегрованих систем підприємств та бізнес-установ різного профілю, а також пристроїв, що забезпечують зв'язок і завжди неминуче знаходяться поруч з нами. Пристрої, які нас оточують всюди, мають не лише набір стандартних програм, які розробник там запровадив. Наприклад, люди, які використовують стандартні методи навігації GPS, ніколи не замислювались про те, як орієнтуватися в торговому центрі, магазині чи на підприємстві. Усі ці організації можуть мати різний розмір за різними будівельними схемами, починаючи від малого бізнесу з кількома десятками людей і закінчуючи великими корпораціями з десятками тисяч працівників. Система інерціальної індивідуальної навігації вирішує такі проблеми, такі системи призначені для вирішення проблем як підприємства в цілому, так і рівня кожної людини. Метою цієї роботи було розробити інерційну пішохідну систему для підрахунку зроблених кроків, а також орієнтації в просторі без зовнішніх даних.In the modern dynamically developing world, a person occupies a leading position, in such conditions the market for complex automated integrated systems of enterprises and business institutions of various profiles, as well as devices that provide communication and always inevitably be near us, is developing. The devices that surround us everywhere have not only a set of standard programs that the developer has introduced there. For example, people who use standard GPS navigation methods never thought about how to navigate in a shopping center and a store, or an enterprise. All of these organizations can be of very different sizes with a variety of construction schemes, ranging from small businesses with a few dozen people to large corporations with tens of thousands of employees. The system of inertial individual navigation solves such problems, such systems are designed to solve the problems of both the enterprise as a whole and the level of each individual. The purpose of this work was to develop an inertial pedestrian system for counting the steps taken, as well as orientation in space without external data

A study on virtual reality and developing the experience in a gaming simulation

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Masters by ResearchVirtual Reality (VR) is an experience where a person is provided with the freedom of viewing and moving in a virtual world [1]. The experience is not constrained to a limited control. Here, it was triggered interactively according to the user’s physical movement [1] [2]. So the user feels as if they are seeing the real world; also, 3D technologies allow the viewer to experience the volume of the object and its prospection in the virtual world [1]. The human brain generates the depth when each eye receives the images in its point of view. For learning for and developing the project using the university’s facilities, some of the core parts of the research have been accomplished, such as designing the VR motion controller and VR HMD (Head Mount Display), using an open source microcontroller. The VR HMD with the VR controller gives an immersive feel and a complete VR system [2]. The motive was to demonstrate a working model to create a VR experience on a mobile platform. Particularly, the VR system uses a micro electro-mechanical system to track motion without a tracking camera. The VR experience has also been developed in a gaming simulation. To produce this, Maya, Unity, Motion Analysis System, MotionBuilder, Arduino and programming have been used. The lessons and codes taken or improvised from [33] [44] [25] and [45] have been studied and implemented

Personal sensor wristband for smart infrastructure and control

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, February 2013."February 2013." Cataloged from PDF version of thesis.Includes bibliographical references (p. 67-72).Despite the rapid expansion of computers beyond desktop systems into devices and systems in the environment around us, the control interfaces to these systems are often basic and inadequate, particularly for infrastructure systems. WristQue is a wearable interface for interacting with computerized systems in the environment, providing both explicit remote control with buttons, touch, and gestural interfaces, and automatic closed-loop control using environmental sensors on the device, fused with precise indoor location for context. By placing these sensors and controls on the wrist, they are generally able to sense the environment unobstructed and are conveniently within reach at all times. WristQue is able to continuously collect and stream sensor data through a wireless network infrastructure, including temperature, humidity, activity, light, and color. A 9-DoF inertial/ magnetic measurement unit can be enabled to use the WristQue as a wrist-based gestural interface to nearby devices. Location and orientation data is used to implement a pointing interface that the user can use to indicate a device to control. This interface was implemented and tested using the WristQue and a commercial UWB localization system. The other sensors on the WristQue were validated by collecting several days of environmental data and conducting several controlled experiments. With these capabilities, the WristQue can be used in a number of sensing and control applications, such as lighting and comfort control.by Brian D. Mayton.S.M