this paper discusses the development of an android based smart automated fluid dispensing and blending system. the developed system confines to juice dispensing and blending application used in food processing. the sy...
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this paper investigates the problem of observer-based controller design for nonlinear networked control systems subject to imperfect communication links. the Takagi-Sugeno (T-S) model is utilized to approximate the no...
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this paper investigates the problem of observer-based controller design for nonlinear networked control systems subject to imperfect communication links. the Takagi-Sugeno (T-S) model is utilized to approximate the nonlinear plant. Boththe imperfect sensor-to-controller and controller-to-actuator links are considered, which are described via two independent Bernoulli stochastic processes. A dynamic compensation strategy is adopted in the controller-to-actuator link. the premise variables of the observer and the controller to be designed depend on the state variables estimated by the observer instead of those of the plant. Moreover, sufficient criteria are obtained to guarantee the resulting closed-loop system to be stochastically stable with H ∞ performance. Finally, a numerical example is provided to illustrate the effectiveness of the methodology proposed in this paper.
sensors are one of the primary building blocks of IoT. Owing to close proximity of physical world, sensors often collect sensitive information. Invariably, sensor data has rich information content. Here we propose a n...
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ISBN:
(纸本)9781450336314
sensors are one of the primary building blocks of IoT. Owing to close proximity of physical world, sensors often collect sensitive information. Invariably, sensor data has rich information content. Here we propose a novel solution IAS: Information Analytics for sensors to unlock massive potential of sensor data through information analytics and demonstrate an alerting mechanism based on criticality of sensor information. ECG anomaly detection for healthcare, unusual appliance operation detection from smart energy meter data, bad road condition as well as activity detection from accelerometer data are typical use-case scenarios. We use robust statistical and information theoretic approaches. Our approach is unsupervised and is completely sensor agnostic. this abstract provides overview of design and implementation of our tool IAS along with obtained results tested on publicly available datasets. Last but not the least, IAS validates that outliers contain most delicate information.
Face recognition is one of the most popular research problems on various platforms. New research issues arise when it comes to resource constrained devices, such as smart glasses, due to the overwhelming computation a...
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ISBN:
(纸本)9781450336314
Face recognition is one of the most popular research problems on various platforms. New research issues arise when it comes to resource constrained devices, such as smart glasses, due to the overwhelming computation and energy requirements of the accurate face recognition methods. In this paper, we have prototyped a robust and efficient sensor-assisted face recognition system on smart glasses by exploring the power of multimodal sensors including the camera and Inertial Measurement Unit (IMU) sensors. Evaluation shows that the prototyped system is up to 10% more accurate than the state-of-the-art face recognition methods while its computational cost is in the same order as an efficient benchmark method (e.g., Eigenface).
Developing analytical applications for IoT based on sensor signal processing tends to be complicated as applications are executed as sequence of steps comprising of multiple alternative algorithms, including suitable ...
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ISBN:
(纸本)9781450336314
Developing analytical applications for IoT based on sensor signal processing tends to be complicated as applications are executed as sequence of steps comprising of multiple alternative algorithms, including suitable feature extraction modules depending on the goal of the application. Experience shows that developers spend considerable time and effort in performing feature extraction and dimensionality reduction. In this paper we propose a framework based on a relevant case study which allows developers to drag and drop algorithms to create a workflow chain, automatically select the most relevant signal features for the particular analytic application using a training data set to generate a model and deploy the model for use. the method reduces the effort and cost of development which is deemed highly important for the analytics industry.
Recognizing user emotional states while running entertainment applications such as playing game or watching video is very important to understand and improve user experience. In this work, we designed a practical syst...
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ISBN:
(纸本)9781450336314
Recognizing user emotional states while running entertainment applications such as playing game or watching video is very important to understand and improve user experience. In this work, we designed a practical system using wearable physiological sensors including skin electrical conductivity and photoplethysmography (PPG) to recognize popular non-negative emotions that people experience when they watch videos or play games on their mobile devices. We demonstrates how our system recognizes emotional states in two phases: (1) classifying the levels of arousal (high or low) and valence (positive or neutral) at the accuracy of 94.74% and 78.95% respectively; (2) recognizing three non-negative emotions: excitement, contentment, amusement by mapping arousal and valence levels using Russel circumplex model of affect.
Operating systems (OS) in wireless sensor nodes can be classified into event-driven systems or multithreaded systems. Most event-driven systems, such as TinyOS, drive down power consumption although context switching ...
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ISBN:
(纸本)9781450336314
Operating systems (OS) in wireless sensor nodes can be classified into event-driven systems or multithreaded systems. Most event-driven systems, such as TinyOS, drive down power consumption although context switching for real-time processing is not available. Among multithreaded systems, non-preemptive systems, such as Protothreads in Contiki, often have lack of real-time processing capability. In Protothreads, if a higher-priority task was posted while a lower-priority task has been running, the lower-priority task cannot be preempted. thus, one challenge is that without changing the semantics of Protothreads, how the system can be preemptive as well as lowering the power consumption for real-time tasks such as target tracking. In this paper, we propose a dynamically switchable scheduling system for operating systems using Protothreads where events with time constraint have occurred. this system enables to trigger interruption, to process real-time tasks preferentially when real-time events occurred, and to save energy by executing tasks except real-time tasks as a standard event-driven system. Exeprimental results show that latency in Contiki is reduced by about 75% in the best case and is kept constant with power efficiency.
In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. the proposed method works for various postures or states namely, standing, sitting, walk...
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ISBN:
(纸本)9781450331432
In this paper authors have proposed a person identification method independent of his position with respect to the input sensor. the proposed method works for various postures or states namely, standing, sitting, walking. this method initially identifies the person's state and separate SVM based models are used for person identification (PI) for each of these three above mentioned states. Copyright 2014 acm.
the commercialization of cheap unmanned aerial vehicles (UAVs) is starting to change the way we, as sensor network system designers, think of data collection. Especially, UAVs provide a third dimension of mobile data ...
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ISBN:
(纸本)9781450336314
the commercialization of cheap unmanned aerial vehicles (UAVs) is starting to change the way we, as sensor network system designers, think of data collection. Especially, UAVs provide a third dimension of mobile data collection as we can now traverse the sky with minimal obstacles, rather than rovering the ground with wheeled robots. However, despite UAVs or drones being an interesting platform withthe potential to change sensor network deployment topologies, little do we understand on how data collection will perform "in the air". In this work we present a preliminary empirical study on the performance of aerial data collection using an IEEE 802.15.4 radio-equipped drone connecting itself to sensor nodes positioned on the ground. Our results show that a drone-based data collection platform outperforms that of an "at ground-level" data collection unit, despite being at identical distances. Based on this study, we identify the increased data collection height and "easy-to-achieve" line-of-sight as key features that make this possible.
this paper describes the components used to build a sensor/ actuator network to control a model railroad layout. Control of the model railroad is accomplished using a network of Digi International XBee modules. Inform...
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ISBN:
(纸本)9781450331432
this paper describes the components used to build a sensor/ actuator network to control a model railroad layout. Control of the model railroad is accomplished using a network of Digi International XBee modules. Information generated by sensors and actions sent to the layout are coordinated using the open source JMRI software package on a general purpose computer connected to the XBee network. Copyright 2014 acm.
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