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Cloud computing (CC) is a computing model that enables its customers to access a shared pool of resources (e.g., storage, network, servers, etc.) through the Internet with a pay-per-use pricing model. Different service models are employed in CC including the Platform-as-a-Service (PaaS) model, in which the costumers request a certain set of resources and the cloud service providers provide these resources...
Internet-of-Things (IoT) is emerging as one of the popular technologies influencing every aspect of human life. The IoT devices equipped with sensors are changing every domain of the world to become smarter. In particular, the majorly benifited service sectors are agriculture, industries, healthcare, control & automation, retail & logistics, and power & energy. The data generated...
This paper presents a novel wearable biomedical Network on Chip (NoC) concept development to monitor and predict irregular brain waves as advanced sensitive portable for an electroencephalogram (EEG) analysis device. The proposed device will monitor brain’s spontaneous electrical activity in normal and abnormal situations for specific patients suffering from different types of epilepsy...
All over the world, the crowd management is a big challenge facing the organizations of any event with large number of people. It is clear that this task is becoming more difficult and complicated when the event is larger. In the recent few years, the there are many new technologies developed that can be utilized in crowed management. Among these new technologies is wireless communications, cloud...
Fifth-generation (5G) control/user (C/U) plane split heterogeneous network may cause more serious handover problems than traditional networks, especially for the inter-macrocell handover. In addition, the mobility behavior of mobile node (MN) may also result in improper handover triggers. In this paper, an adaptive handover trigger strategy (AHTS) is proposed to predict the received signal strength...
Reliable and efficient spectrum sensing through dynamic selection of a subset of spectrum sensors is studied. The problem of selecting K sensor measurements from a set of M potential sensors is considered where K
Recent studies have shown that autistic children tend to speak and interact more with an interactive robot. Unfortunately, due to the high deployment cost, many robotic experiments were still conducted in highly controlled clinical or home settings. Hence, a low cost robot needs to be designed to benefit families with autistic children. In Summer 2014, we have designed a low cost robot, LILI version...
Battery-free sensor networks are an emerging field with very promising applications. Passive sensors without batteries can resist extreme conditions and can be placed in practically any location, and do not need replacement for a long time. They are the perfect candidates for some of the applications we propose in this paper. Currently they are being used for structure analysis, assembly line control,...
Target discrimination in wireless sensor networks remains challenging when sensors have structured electronic noise and deployment settings have variable in-situ clutter. Datadriven learning of discrimination functions is especially hard when deployment sites are remote or hazardous, necessitating reliance on surrogate environments for data collection. The challenge is exacerbated if sensors are resource...
Scalability is a major issue for Internet of Things (IoT) as the total amount of traffic data collected and/or the number of sensors deployed grow. In some IoT applications such as healthcare, power consumption is also a key design factor for the IoT devices. In this paper, a multi-signal compression and encoding method based on Analog Joint Source Channel Coding (AJSCC) is proposed that works fully...
In this paper, the problem of target localization in the presence of outlying sensors is tackled. This problem is important in practice because in many real-world applications the sensors might report irrelevant data unintentionally or maliciously. The problem is formulated by applying robust statistics techniques on squared range measurements and two different approaches to solve the problem are...
In this paper, we study vision-based localization for robots. We anticipate that numerous mobile robots will serve or interact with humans in indoor scenarios such as healthcare, entertainment, and public service. Such scenarios entail accurate and scalable indoor visual robot localization, the subject of this work. Most existing vision-based localization approaches suffer from low localization accuracy...
Multi-level clustering offers the scalability that is essential to large-scale ad hoc and sensor networks in addition to supporting energy-efficient strategies for gathering data. The optimality of a multi-level network largely depends on two design variables: 1) The number of levels, and 2) The number of nodes operating at each level. We characterize these variables within a multi-hop, multi-level...
The design and deployment of networked embedded systems is challenging. In particular, the environment in which the system operates has a severe impact on the final performance. Existing tools trade generality for specificity with arbitrary setups, e.g., in simulation, or specific configurations, e.g., in public testbeds. As a result, the peculiar effect of the target deployment scenario on the system...
While bringing massive-scale sensing at low cost, mobile participatory sensing is challenged by the low accuracy of the sensors embedded in and/or connected to the smartphones. The mobile measurements that are collected need to be corrected so as to accurately match the phenomena being observed. This paper addresses this challenge by introducing a multi-hop, multiparty calibration method that operates...
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
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