pollution control is based on correctly measuring pollutant concentrations but, at the moment,the principal european cities only monitor pollution levels by means of a few fixed stations co-located inselected points of the urban layout far from hotspots and/or by means of meteorological prediction models offuture pollution. few cities integrate the information from both sources. the implementat...

recently different approaches have been developed in the field of sensor fault diagnostics based on auto-associative neural network (aann). in this paper we present a novel algorithm called self reconstructing auto-associative neural network (s-aann) which is able to detect and isolate single faulty sensor via reconstruction. we have also extended the algorithm to be applicable in multiple faul...

This paper introduces Artificial Neural Network (ANN) method for measuring voltage in the Optical Voltage Transducer (OVT) using one or more electric field sensors. In order to obtain an accurate voltage measurement with minimum number of sensors, first the locations of sensors are specified by quadrature method. Then the electric field intensity at these locations is provided to ANN for the ca...

Routing is an important challenge in WSN due to the presence of hundreds or thousands of sensor nodes. Low Energy Adaptive Clustering Hierarchy (LEACH) is a hierarchical routing and data dissemination protocol. LEACH divides a network domain into several sub-domains that are called clusters. Non-uniformity of cluster distribution and CHs selection without considering the positions of other sens...

nowadays, wireless sensor network has been of interest to investigators and the greatest challenge in this part is the limited energy of sensors. sensors usually are in the harsh environments and transit in these environments is hard and impossible and moreover the nodes use non- replaceable batteries. because of this, saving energy is very important. in this paper we tried to decrease hard and...

One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...

Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple faul...

A sensor network is made up of a large number of sensors with limited energy. Sensors collect environmental data then send them to the sink. Energy efficiency and thereby increasing the lifetime of sensor networks is important. Direct transfer of the data from each node to the central station will increase energy consumption. Previous research has shown that the organization of nodes in cluster...