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This work proposes an ANN based method for fetal heart rate monitoring. Various measurements are taken and given as input to the ANN based classifier to detect fetal health such as ‘Normal’, ‘Suspect’ and ‘Pathologic’. All the design and simulation works are carried out with MATLAB software. ANN based classifier is trained with data from various recordings of cardiotocography. After the network is...
This paper considers architecture and functionality of the embedded data acquisition system for automated beehive monitoring. A description of constructed sensor subsystems is given. Proposed solution acquires hive temperature, humidity and weight referring this data to the mobile application via wireless network. The system also performs an analysis of collected bee noises with artificial neural...
The article deals with the application of remote sensing of agricultural plantations for assessment of their nitrogen fertilizer provision. The basic technologies of remote sensing used today, their advantages and disadvantages are described. A new calibration method for images obtained from sensors placed on the platform of UAV in unstable illumination based on EXIFF data file, such as size Light...
This paper is using artificial neural network (ANN) to predict oxygen content in the water for the fish farm, so that decrease times of starts of oxygen suppliers. In Southern Taiwan, aquaculture is one of major economic industries. Especially, the important issue is how to effectively monitor the oxygen content in the water, so that the fish will not die and start the oxygen suppliers for the minimum...
The critical requirements for devices connected in Internet of Things (IoT) are long battery life, long coverage range, and low deployment cost. In our previous work, we developed cognitive controller for controlling the HVAC of non-domestic building using short range communication in an unlicensed spectrum (915 MHz). In this work, we have upgraded our cognitive controller with recently developed...
The dams are very important objects (production of electric energy, flood management, drought control, etc.) but they are also a great danger for areas downstream because there is always risk of dam failure. To prevent dam failure it is important to perform regular dam monitoring. Precise geodetic surveying of a number of discrete points, which accurately depict the characteristics of the dam, is...
Detailed energy consumption information of household appliance is meaningful for the demand side management (DSM) and home energy conservation. In this paper, a novel non-intrusive load monitoring (NILM) method is proposed for residential energy management systems(REMS). Unlike existing NILM techniques, this method works effectively with very few smart meter measurementparameters obtained at a low...
According to the demands of monitoring method for animal transports, this paper proposes the use of a BP neural network based algorithm to monitor the animal transports, using the wireless sensor network to monitor the environment during transport to assure the animal welfare. The algorithm requires data collection on the transportation cage with respect to temperature, humidity, air pressure, vibration...
A Nonintrusive load monitoring (NILM) system is an energy demand monitoring and load identification system that only uses one instrument installed at main power distribution board. In this paper authors have used low sampling rate of monitored data to detect any change of power signal that obtained a 1 Hz sampling rate of active power from energy meter. Using Artificial Neural Network (ANN) for training...
In this paper a new approach for safety monitoring of dangerous gases in the industrial plants is proposed. A single artificial neural network is used for determination of the gas concentrations based on sensor array measurements, performing at the same time compensation of the temperature and humidity influence on the sensor outputs. The obtained results show good accuracy in gas concentration estimation,...
It is well known that ancient buildings suffer a high vulnerability to hazards, which may induce unpredictable damages. For this purpose, a main objective to be pursued concerns with the development of techniques for monitoring historical buildings and immediately alerting in case of early vulnerability warnings. This paper proposes a noninvasive Neural Network-based (NN-based) approach for Monitoring...
This paper investigates the traffic data in holidays within Zhejiang province in Shenhai freeway from the spatial and temporal aspects. The results shows that Tangxia monitoring site has a much higher flow than other sites which indicates a heavy traffic jam in holidays. A further Investigation of traffic flow in Tangxia site shows a common higher traffic flow in the north direction compared with...
Artificial Neural Network is becoming an efficient tool in online structural health monitoring. ANN enables, due to its promising inherent capabilities, to predict existence of undesirable effects such as cracks within the structure. Natural frequencies of the structure particularly the first three vibration modes are the most pronounced features of the structure to be evaluated for the health monitoring...
In Machine Learning applications, the selection of the classification algorithm depends on the problem at hand. This paper provides a comparison of the performance of the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) for food intake detection. A combination of time domain (TD) and frequency domain (FD) features, extracted from signals captured using a jaw motion sensor, were...
There is a relation, not always linear, between the blood pressure and the pulse duration, obtained from photoplethysmography (PPG) signal. In order to estimate the blood pressure from the PPG signal, in this paper the Artificial Neural Networks (ANNs) are used. Training data were extracted from the Multiparameter Intelligent Monitoring in Intensive Care waveform database for better representation...
The problem of automating the detection and classification of intruders in vast and hard to reach terrains has been an active research topic over the past decade. In this paper we present a new paradigm of intrusion detection and classification by combining the sensing potential of self-configuring and instantly-deployable wireless sensor networks (WSN's) with the reasoning capabilities of artificial...
The prestressed loss of group anchor in rock slope increase with time, which leads to the compression belt of structure plane in group anchor area was weakened, deformation of rock surface toward the free surface direction increase gradually, as a result, the slope stability was drastically reduced. Based on the group anchor layout of the abutment rock slope of an arch dam, the anchor-hold monitoring...
The demand of power and the size and complexity of the power system is increasing. Wide area monitoring and control is an integral part in transitioning from the traditional power system to a Smart Grid. However, wide area monitoring becomes challenging as the size of the electric power grid, and consequently the number of components to be monitored, grows. Wide area monitor (WAM) designed using feed-forward...
In the 1980s and at the turn of last century, severe global waves of sovereign defaults occurred in less developed countries. To date, the forecasting and monitoring results of debt crises are still at a preliminary stage, while the issue is at present highly topical. This paper explores whether the application of the Self-organizing map (SOM), a neural network-based visualization tool, facilitates...
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