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Inspired by open source software development model of utilizing intelligence and memory of mutually sharable human resources at almost negligible financial cost we develop framework to use perception and cognition of crowd. The paper presents a survey of recent such approaches, associated limitations and scopes of impoverishment. Using inclusive design framework, we design web and android applications...
With the enhanced computing capabilities and a wide variety of functions available on smartphones, critical and sensitive information, such as contact lists, messages, schedules, credit card numbers, is stored on smartphones, which makes preventing smartphone from being stolen of an unprecedented importance. Loss of smartphones not only causes economic loss but also jeopardizes the privacy of the...
This paper proposes a critical survey of crowd analysis techniques using visual and non-visual sensors. Automatic crowd understanding has a massive impact on several applications including surveillance and security, situation awareness, crowd management, public space design, intelligent and virtual environments. In case of emergency, it enables practical safety applications by identifying crowd situational...
In the recent years the Smart City paradigm has gained interest worldwide. Services are built on top of data sensed in the city and then analyzed in order to enhance people's quality of life. Nowadays users are also able to participate in such a data gathering, mostly thanks to a reduction in the cost of the sensing devices. Moreover, smartphones encompass many useful sensors and can be leveraged...
This paper proposes an autonomous self-parking system in specific parking area. In this system, the vehicle can drive itself and find the parking spaces to park automatically using a smartphone. The system consists of parking place searching, steering control, path tracking and wireless communication. According to the type of the parking space which has recognized by ultrasonic scanning, the system...
Doze mode, which was introduced from Android 6.0 aiming at reducing battery consumption when the device is unused for a long time. This work firstly reveals the internal details of the battery-saving feature, especially about the state transitions. Furthermore, we discover several defects in Android's device drivers associated with doze mode. By exploiting the defects, we implement various proof-of-concept...
In this research we present a remote localization technique as an essential preprocessing step to enable Physical Analytics in the retail and hospitality sector. We studied two crowdsourced Wi-Fi data sources as potential inputs for fingerprinting-based positioning systems. These sources are non intrusively crowdsourced and can be easily acquired at almost any retail store. We evaluated our hypothesis...
Mobile location-based services (LBSs) empowered by mobile crowdsourcing provide users with context- aware intelligent services based on user locations. As smartphones are capable of collecting and disseminating massive user location-embedded sensing information, privacy preservation for mobile users has become a crucial issue. This paper proposes a metric called privacy exposure to quantify the notion...
In this paper we focus on the problem of human activity recognition without identification of the individuals in a scene. We consider using Wi-Fi signals to detect certain human mobility behaviors such as stationary, walking, or running. The main objective is to successfully detect these behaviors for the individuals and based on that enable detection of the crowd's overall mobility behavior. We propose...
Modern smartphones are nowadays equipped with a multitude of sensors, which extend their capabilities paving the way for a multitude of services. Among these, the ability to locate the device is exploited by many. While outdoor the GPS provides good accuracy, indoor localization is challenging to be performed with it, as buildings shadow the satellite signal. In particular, the barometric pressure...
Since GPS signal is not applicable indoors, vehicle tracking has proven a hassle in underground parking structures. Recent solutions highly rely on floor map to constraint inertial sensors noises. In this paper, we propose VeMap, a road map construction system using only smartphones inside vehicles. It saves effort-intensive and time-consuming business negotiations with building operators, and expensive...
Mobile Crowd Sensing (MCS) is a technique that aims to obtain the participation of volunteers willing to use their smartphones to harvest large quantities of data as they move in urban areas. Those volunteers typically move inside a limited area and can encounter other volunteers during their day activity. From the number and duration of their encounters, it is possible to categorize relations between...
Automatic mechanical robots can perform tasks in different environmental conditions that are tedious, monotonous and sometimes hazardous for human beings. These robots can help in mitigating the risk to precious human lives, and also function as substitute for humans to perform some routine, and arduous tasks that need long hours. A Multimodal Smart Amphibot (MSA) proposed in this paper is an example...
Both GPS and WiFi based localization have been exploited in recent years, yet most researches focus on localizing at home without environment context. Besides, the near home or workplace area is complex and has little attention in smart home or IOT. Therefore, after exploring the realistic route in and out of building, we conducted a time localization system (TLS) based on off-the-shelf smart phones...
Bluetooth Low Energy (BLE) has recently positioned itself as one of the key enabling technologies in the Internet of Things (IoT). In order to provide scalability, one promising way to collect data from BLE sensors is to utilize the existing population of smartphones in their range as relays to the cloud. In this case, providing reliable data transfer becomes complicated due to challenges such as...
The tracking of the activities of daily living (ADL) may have significant implications in healthcare because it would enable healthcare professionals to receive updates remotely regarding the functional status of post-injury and post-surgery patients, and people with disabilities and the elderly. If successful, technologies that enable ADL tracking could dramatically reduce the healthcare cost because...
Wearable sensors for heart-rate, ECG, blood pressure, and blood glucose are gaining increasing prominence in home-based healthcare. Though the medical sensory data is now routinely encrypted and signed, the timestamp associated with the data, which is needed for accurate correlation and reconstruction of medical events, remains poorly secured. In this paper we first motivate the problem by demonstrating...
Opportunistic real time mobile crowdsensing pertains to the instantaneous monitoring of large scale phenomena by leveraging human mobility and smartphones' sensors. However, while urban applications concern more about coverage quality and timeliness of detected data, mobile users should care about their consumed energy for performing a sensing task. In this paper, we introduce the Real time OPportunistic...
With diabetes patients doubling every year especially in the UAE there is a need to curb this epidemic and help those who are affected to live an active life. Continuous monitoring of health indicators ensures prompt medical attention and reduction in fatalities. The primary challenge to continuously monitor diabetes is that glucose level measurement requires invasive methods. Moreover, continuous...
Inferring activities on smartphones is a challenging task. Prior works have elaborated on using sensory data from built-in hardware sensors in smartphones or taking advantage of location information to understand human activities. In this paper, we explore two types of data on smartphones to conduct activity inference: 1) Spatial-Temporal: reflecting daily routines from the combination of spatial...
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