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Driving needs the driver to be in a proper condition, aware enough of the road to ensure safety. Driving under the influence of alcohol has been one of the worst cause of traffic accidents worldwide. In this paper, we propose a novel system to detect the awareness of car drivers when driving, which is related to driving under alcohol (drunk driving). The system will be installed in Android smartphones...
One of fields that takes advantage of IoT is home automation. Home automation uses different types of network protocols such as Wi-Fi, Bluetooth and ZigBee. However, existing home equipment often requires network communication enabled power plugs or devices that has a unique communication protocol specified by the company. Although these equipment have standard communication capabilities, each device...
This study examined the behavioral biometrics of smartphone motion to determine potential authentication accuracies on Android phones. The study used machine learning algorithms to analyze data from the accelerometer and gyroscope sensors. Android smartphone data were captured from sixty different individuals, resulting in a large collection of datasets for training and testing. The data were filtered...
The proliferation of powerful mobile devices, along with the increasing demand of location information, has driven the researches to develop positioning applications with higher accuracy. In this paper, we build an Android application which achieved the aim of seamless positioning between the inside and the outside. The system contains four parts: outdoor positioning, which uses GPS and Baidu Map,...
Applications in Smart City context are improving the quality of life of citizens through several technological interactions. These interactions can be also used to relate the citizens' emotions to city's areas. Thus, the main objective of this work is to present a smart phone application that analyzes the citizens' emotions and the relations between these parameters and different city's areas. Daily...
In this paper, we propose a trajectory reconstruction method based on a low-cost IMU (Inertial Measurement Unit), which is usually equipped in smartphones. The IMU used in our work consists of a 3-axis accelerometer and a 3-axis gyroscope, which can record information of acceleration and rotation, respectively. However, intrinsic bias and random noise cause unreliable IMU signals. Thus, to improve...
In this paper, an indoor office locator system is developed. The product developed uses body sensors to detect incoming objects using indoor positioning tracking algorithm which run on a server application to guide the user in an office environment were designed and developed. It is shown that overall the final system allowed a partially blind user to navigate the office with relative safety and accuracy.
With the increasing popularity of the Internet of Things applications, investors are more willing to invest on small digital electronic products and seek business opportunities. At the same time, along with the improvement of the data processing method, people want to get more accurate data. This paper presents an application that using Arduino and Bluetooth electronic scale to connect to smart phones...
Existing smartphone authentication methods (e.g., PIN) typically provide one-time identity verification, but the verified user is still subject to session hijacking or masquerading attacks. This paper presents a framework and performance analysis of a sensor-based smartphone authentication system that continuously verifies the presence of a smartphone user. When a user touches the smartphone screen,...
With the rapid increasing of smart phones and their embedded sensing technologies, mobile crowd sensing (MCS) becomes an emerging sensing paradigm for performing large-scale sensing tasks. One of the key challenges of large-scale mobile crowd sensing systems is how to effectively select the minimum set of participants from the huge user pool to perform the tasks and achieve certain level of coverage...
The emergence of wireless technologies and powerful mobile devices has opened up opportunities for real-time remote health monitoring. Smartphones, equipped with wireless connectivity features and powerful processing capabilities, are usually utilized as a data aggregation, transmission and communication nodes. However, the main challenge of unobtrusive continuous sensing remains fast battery depletion...
Limited research efforts have been made for Mobile CrowdSensing (MCS) to address quality of the recruited crowd, i.e., quality of services/data each individual mobile user and the whole crowd are potentially capable of providing, which is the main focus of the paper. Moreover, to improve flexibility and effectiveness, we consider fine-grained MCS, in which each sensing task is divided into multiple...
Mobile Crowd Sensing (MCS) is an emerging paradigm that exploits the ubiquity of smartphones and cheap sensor devices to collect data and thus contribute to the provision of useful services, especially in the domains of urban life. While many MCS implementations have been proposed for different applications, the lack of common performance metrics means that their efficiency cannot be easily compared...
Recently smartphones are used every area in day-to-day life. Smartphones comes with several built-in sensors like gyroscope, accelerometer etc., along with powerful processing units. There exist various frameworks which use mobile as sensing device and mobile sensors as data extractor and process extracted data to calculate various parameter. This processing unit can be resided either in mobile side...
Smart mobile devices are variously used in the health sector. Some mobile applications empower patients to better understand their health problems, others guide them in health behavior. Moreover, smart mobile devices can be used in clinical research. Mobile crowd sensing has proven high usefulness for collecting health data with high ecological validity in this context. As the core idea, individually...
The futuristic smart cities must have the capabilities to withstand the growing challenges on the urban infrastructure in terms of public safety, resource management, co-operative mobility management and more. To tackle these challenges, the cities are increasingly using next generation information and communication technologies (ICT). A plethora of the ICT based innovations are taking place on a...
Indoor environments are characterized by the existence of various pollutant sources. Moreover, at present, people spend more than 90% of their time inside buildings. Thus, the indoor air quality is undoubtedly a key factor to be controlled to ensure the health and comfort of the occupants. Most of the air quality monitoring systems on the market are very expensive and only allow to collect random...
The reliability of location-based services (LBS) is strongly dependent on the accuracy of the location of the users. However, existing LBS systems are not able to efficiently validate the position of users in large-scale outdoor environments, leading to possible location spoofing attacks by malicious users. To this end, we present an efficient and scalable Location Validation System (LVS) that secures...
This paper presents our recent work on human activity detection based on smart phone sensors and incremental clustering algorithms. The proposed unsupervised (clustering) activity detection scheme works in an incremental manner, which contains two stages. In the first stage, streamed sensor data will be processed. A single-pass clustering algorithm is used in order to generate pre-clustered results...
A recent literature review shows that approximately 20–50% of energy/cost savings are possible in office buildings when accurate occupancy information is applied to the control of building energy systems. Implicit occupancy sensing, by extracting occupancy data from systems already in the building rather than from those explicitly designed to collect occupancy information, has the potential to provide...
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