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Source publication
In this paper, we propose a set of experiments for evaluating sensors’ precision in measuring received
signal strength indicator (RSSI) in wireless sensor networks (WSN). More specifically, a WSN application
is implemented for collecting RSSI measurements in different conditions. The application consists of two
parts: an experiment control script w...
Context in source publication
Context 1
... are several state machines running concurrently: one state machine controlling the experiment control script, and one state machine for each experiment sensor. The state machine for the experiment control script behavior is illustrated in Figure 3, and consists of the following states: ...
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As sensor nodes have limited sensing and transmission capability, their efficient deployment takes an important role in proper monitoring of the critical targets in various applications of wireless sensor networks (WSNs). The key issues that need to be taken care during deployment are the lesser number of deployed sensors, coverage of the targets,...
Citations
... In the field of wireless transducer networks 17 , hardware abstraction for a wide range of commercially available nodes, with several communication protocols and a library of reusable components, represents a more generic and application-independent approach, but not matching the above on-site concentrated requirements. In 22 , the firmware is running on a Tmote Sky sensor 23 , controlled by TinyOS 24 , a popular and widely used operating system for wireless sensor networks. A radio-frequency wireless data acquisition system was developed in 25 , with a set of sensors for measuring meteorological parameters. ...
A flexible firmware architecture for different kinds of data acquisition systems, ranging from high-precision bench instruments to low-cost wireless transducers networks, is presented. The key component is a multi-behaviors finite state machine, easily configurable to both low- and high-performance requirements, to diverse operating systems, as well as to on-line and batch measurement algorithms. The proposed solution was validated experimentally on three case studies with data acquisition architectures: (i) concentrated, in a high-precision instrument for magnetic measurements at CERN, (ii) decentralized, for telemedicine remote monitoring of patients at home, and (iii) distributed, for remote monitoring of building’s energy loss.
Livestock and poultry production and supply is one of the significant food sectors in which more production can lead to a decrease in dependence on exports and earning foreign exchange. Poultry farming is a vital industry for sustainable food supply in all countries. In this research, intelligent applications and solutions in the poultry industry are identified and prioritized using the simultaneous evaluation of criteria and alternatives (SECA) method based on criteria representing the sustainable development. Analysis showed that eighteen principal fields of intelligent solutions are identified in the poultry industry. The weights obtained for sustainable development criteria based on the SECA method are economic (0.351), social (0.3383), and environmental (0.3065) in order of value. Economic sustainability should be most important in implementing smart solutions-based projects in the poultry industry. One of the main challenges of the agricultural sector, especially the poultry industry, is traditional production utilization which leads to the overuse of land capacity. Globalization trends, climate changes, moving from a fossil fuel-based economy to an environment-based economy, competition for land, freshwater, and labor shortage have also led to more complications in supplying nutrition. Considering the potential of smart solutions in realizing sustainable development objectives, it is suggested to focus more on the environmental aspects of poultry industry projects.
