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In the recent years, wireless communications are extremely useful in many disciplines including health monitoring, environment monitoring, signal processing etc. State estimation and prediction are quite challenging tasks in wireless communications. Traditionally, in the literature, dynamic state-space models have been used for the state estimation and predic- tion purpose. The estimation method is based on Kalman-Filter which is computationally demanding. In this work, we consider computationally simpler Gibbs sampler algorithm for the state estimation. We consider three different cases, (i) continuous state values, (ii) binary (0/1) state values, and (iii) categorical state values with more than two categories. We consider a simple linear model for the prediction purpose, and the underlying regression coefficients are estimated by Gibbs sampler. We compute the misclassification proportions for assessing the practical usefulness of our estimation approach. Areal dataset where 200 wireless sensor nodes are used for measuring the temperature of a chamber is analysed in this work
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In this paper, consumption of energy by the sensor nodes in Wireless Sensor Nodes (WSNs) is been handled effectively using light weighted tree shaped dynamic routing protocol. The main objective is to improve the network lifetime with higher rate of energy consumption. The proposed network routing protocol is utilized to fix the routing problems related to mobile base stations in infrastructural network. The protocol is designed in such a way that it avoids centralized router or mobile base station to control the entire mobile sensor nodes access. The evaluation of proposed method is tested against various result metrics over conventional energy efficient algorithms. The results prove the effectiveness of proposed algorithm against conventional routing algorithm over WSNs.
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ABSTRACT Smart Health Surveillance system is to measure and display the Electrocardiogram (ECG) and temperature of patient's body continuously and also to communicate to the doctor. The system measures ECG using infrared sensor and the temperatures at oral and wrist of the patient using temperature sensors. Microcontroller, receives the data from the sensors, displays the same and communicates to the web server automatically. In the existing system, patient's vital parameters are obtained and the obtained values are entered into database and then uploaded into a web-based server manually. The existing system has no alert signal, during abnormal condition to the surrounding and to the doctor. The proposed system consists of a visualization module of the server program, which graphically displays the recorded biomedical signals on android mobile devices used by doctors at the receiver end. It also gives a buzzer or an alarm in case of abnormal condition of the patient.
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ABSTRACT The primary challenge in organizing sensor networks is energy efficacy. This requisite for energy efficacy is because sensor nodes capacities are limited and replacing them is not viable. This restriction further decreases network lifetime. Node lifetime varies depending on the requisites expected of its battery. Hence, primary element in constructing sensor networks is resilience to deal with decreasing lifetime of all sensor nodes. Various network infrastructures as well as their routing protocols for reduction of power utilization as well as to prolong network lifetime are studied. After analysis, it is observed that network constructions that depend on clustering are the most effective methods in terms of power utilization. Clustering divides networks into inter-related clusters such that every cluster has several sensor nodes with a Cluster Head (CH) at its head. Sensor gathered information is transmitted to data processing centers through CH hierarchy in clustered environments. The current study utilizes Multi-Objective Particle Swarm Optimization (MOPSO)-Differential Evolution (DE) (MOPSO-DE) technique for optimizing clustering.
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Purpose: To enhance speedy communication between the patient and the doctor through newly proposed routing protocol at the mobile node. Materials and Methods: The proposed model is applied for a telemedicine application during disaster recovery management. In this paper, Energy Effi cient Link Stability Routing Protocol (EELSRP) has been developed by simulation and real time. This framework is designed for the immediate healing of affected persons in remote areas, especially at the time of the disaster where there is no hospital proximity. In case of disasters, there might be an outbreak of infectious diseases. In such cases, the patient’s medical record is also transferred by the fi eld operator from disaster place to the hospital to facilitate the identifi cation of the disease-causing agent and to prescribe the necessary medication. The heterogeneous networking framework provides reliable, energy effi cientand speedy communication between the patient and the doctor using the proposed routing protocol at the mobile node. Results: The performance of the simulation and real time versions of the Energy Effi cient Link Stability Routing Protocol (EELSRP) protocol has been analyzed. Experimental results prove the effi ciency of the real-time version of EESLRP protocol. Conclusion: The packet delivery ratio and throughput of the real time version of EELSRP protocol is increased by 3% and 10%, respectively, when compared to the simulated version of EELSRP. The end-to-end delay and energy consumption are reduced by 10% and 2% in the real time version of EELSRP.
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Many applications of wireless sensor networks can benefit from fine-grained localization. In this paper, we proposed an accurate, distributed localization method based on the time difference between radio signal and sound wave. In a trilateration, each node adaptively chooses a neighborhood of sensors and updates its position estimate with trilateration, and then passes this update to neighboring sensors. Application examples demonstrate that the proposed method is more robust and accurate in localizing node than the previous proposals and it can achieve comparable results using much fewer anchor nodes than the previous methods.
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Many applications of wireless sensor networks can benefit from fine-grained localization. In this paper, we proposed an accurate, distributed localization method based on the time difference between radio signal and sound wave. In a trilateration, each node adaptively chooses a neighborhood of sensors and updates its position estimate with trilateration, and then passes this update to neighboring sensors. Application examples demonstrate that the proposed method is more robust and accurate in localizing node than the previous proposals and it can achieve comparable results using much fewer anchor nodes than the previous methods.
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The co-channel interference (collisions) seriously affect the transmission for the newly deployed wireless sensor networks since there is no structure at that phase. In this paper, the interference of the whole network is analyzed based on the SNIR model. The new concept of critical transmitting range is proposed, based on which the transmission theorem is obtained and proved. The results provide the theoretical ground to set up the primary structure of newly deployed networks.
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The co-channel interference (collisions) seriously affect the transmission for the newly deployed wireless sensor networks since there is no structure at that phase. In this paper, the interference of the whole network is analyzed based on the SNIR model. The new concept of critical transmitting range is proposed, based on which the transmission theorem is obtained and proved. The results provide the theoretical ground to set up the primary structure of newly deployed networks.
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Objective To design a system for monitoring pulse wave transit time (PWTT) in working condition non-intrusively and continuously. Method The system was composed of wireless ECG sensor and wireless pulse wave sensor which measure pulse wave signal from the temporal artery and ECG signal from body synchronously and calculates PWTT continuously. Result Both the wireless ECG sensor and the wireless pulse wave sensor were small sized and powered by button battery. And the accuracy of time synchronization about sensors was less than 1 ms. The calculated PWTT changed slowly with deep breathing. Conclusion The system works smoothly for continuous monitoring of PWTT in working condition.
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Objective To monitor the hospital computer room in real time; ensure the normal running of hospital information system; overcome the disadvantages of wired monitor system. Methods Zigbee was used to build a wireless sensor network. Wireless monitor system for hospital computer room was realized. Results By exerting the advantages of zigbee, hospital computer room was monitored more effectually and the workload of the computer room keeper was reduced. Conclusion Using Hospital computer wireless monitor system based on zigbee can achieve the uniform management and monitoring effectually.
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War-fighter Physiologic Status Monitoring(WPSM)is a wireless sensor network that is used to collect,transmit,store and interpret physiologic data from soldiers,sailors and pilots.It can collect and monitor information regarding vital signs such as body temperature,heart rate,blood pressure,hydration and stress levels,sleep status,body position and workload capacity of the warrior.If necessary,the WPSM can notify medics and commanders if the soldier has been wounded or has become fatigued.The structure of the wireless sensor network in the WPSM and the data management of the sensor network are mainly discussed.