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By the virtue of blooming automation industry and wireless connectivity, all the devices within the home can be connected. This improves the comfort, energy efficiency, indoor security, cost savings of the home. Small and constrained embedded devices are used to remotely monitor the conditions within home and control the home appliances. In such case, power consumption and network bandwidth become...
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...
Crowdsensing recently attracts great attention from both industry and academia. By fusing and analyzing multi- dimensional sensing data collected from crowdsensing users, it is possible to support health caring, environment mentoring, traffic mentoring and social behavior mentoring. Nonetheless, how to preserve users' data privacy during data fusing, e.g., data aggregation, has been rarely discussed...
In this paper, we propose to learn LIfestyles of mobile users via mobile Phone Sensing (LIPS), and we develop a system and algorithms to realize this idea. First, we present the workflow and architecture of our system, LIPS. Combining both unsupervised and supervised learning, we propose a hybrid scheme for lifestyle learning, which consists of two parts: characterization and prediction. Specifically,...
Parking-management systems, including services that recognize vacant stalls, can play a valuable role in reducing traffic and energy waste in large cities. Visual methods for detecting vacant parking spots are cost-effective options since they can take advantage of the cameras already available in many parking lots. However, visual-detection methods can be fragile and not easily generalizable. In...
With the proliferation of mobile devices, spatial crowdsourcing is rising as a new paradigm that enables individuals to participate in tasks related to some locations in the physical world. Nevertheless, how to allocate these tasks to proper mobile users and improve communication efficiency are critical in spatial crowdsourcing. In this paper, we propose Fo-DSC, a fog-based deduplicated spatial crowdsourcing...
In this paper, we investigate the problem of robust congestion control in infrastructure-based cognitive radio networks (CRN). We develop an active queue management (AQM) algorithm, termed MAQ, based on multiple model predictive control (MMPC). The goal is to stabilize the TCP queue at the base station (BS) under disturbances from the varying service capacity for secondary users (SU). The proposed...
Exploiting the network's edge is trending nowadays due to the evolution end devices, e.g., IoTs and smartphones. In this work, we present LAMEN1, an initial attempt to execute services at the network's edge closer to data sources. Unlike crowdsensing approaches, which use end devices as data collectors wasting the bandwidth in transmission to cloud servers for processing. LAMEN proposes a layered...
In the automotive area we have in our days a number of simulation environments that reproduce the dynamical characteristics of a vehicle in a very realistic way. These environments cannot be easily used in other domains or applied on complex, coupled machines for example ride-lawn mowers, for several reasons. On one hand the heterogeneous vegetation that has to be processed by the engine is influencing...
With the rapid development of portable mobile devices, crowd sensing systems have been recognized as a key technology to utilize the data collected by the portable mobile devices towards scalable and flexible mobile services. However, since the information provided by devices may not be reliable, the aggregated results of the collected data may not be accurate. To tackle this challenge, various truth...
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...
Analyzing and visualizing large datasets generated by real-time spatio-temporal activities (e.g. vehicle mobility or large crowd movement) are a very challenging task. Recursive delays both at middleware and front end applications limit the of usefulness of the real-time analysis. In this paper, we present a framework “Spatial-Crowd” that first handles spatial-temporal data acquisition and processing...
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...
In order to realize the function of accurate measurement, multipoint collection and wireless transmission on various environmental monitoring factors in the workshop, a workshop environment monitoring system is proposed based on the technology of internet of things. A number of wireless monitoring nodes are set up in each workshop to collect a variety of environmental information, then transmit the...
In this paper we describe an environmental system that has been developed to provide monitoring of pollutants. Unlike other work in the literature this system allows the collection and location-pinning of data to be carried out indoors as well as outdoors. The mixed indoor and outdoor data collected from different users can be classified into individual category using K-Means algorithm for further...
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...
The wide spread of smart mobile devices such as tablets and phones makes mobile crowdsensing a viable approach for collecting data and monitoring phenomena of common interest. Smart devices can sense and compute their surroundings and contribute to mechanisms that examine social and collective behaviours. Crowdsensing offers a feasible alternative to exchange and compute sensing tasks and data between...
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...
Eel is a high economic value commodity. International market demand for this fish is high enough, so a lot of farmers cultivated it with main objective of export. The problem in eel fish farming is the seeds that have to be taken directly from nature. This impacts to the more rapidly declining of eel seeds availability. Another problem in the cultivation of eels is how to control and create environments...
The Wireless Body Area Network (WBAN) is emerging by leaps and bound due to tremendous evolutions in sensors and wireless communication technologies. For WBAN technology improvisation, researchers are mainly concentrating on technical parameters of health monitoring to make it interactive and real time based. A WBAN is an integration of Wireless Sensor Networks (WSNs) to connect various Biomedical...
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