Intelligent Humidity Sensor for Wireless Sensor Network Agricultural Application

Abstract

Wireless Sensor Networks (WSN) is now widely used in precision agriculture applications. Sensors play an important role in WSN.The traditional humidity sensors employed in the agriculture have a drawback that they acquire a large amount of data which is to be transmitted or processed. Whereas the intelligent sensor proposed in this paper uses a conventional sensor and an embedded processor that can process the data acquired using algorithms to reduce the amount of data collected, to extract only relevant information and to present this information in a format which minimizes post-processing latency. As a result of which the final processing end has to perform a little computation that too only on features (like significant changes in humidity) rather on the huge data hence reducing the power consumption. The intelligent humidity sensor reduces the amount of data processed by 50% (depending upon humidity variations) and thereby also reducing the power consumption.

Designing efficient soil resistivity measurement technique for agricultural wireless sensor network

“…In their paper, they have also focused on avoiding landslides under heavy rainfall. Shinghal et al 15 have designed an intelligent wireless sensor network (WSN) for measuring humidity in agricultural fields. They have incorporated an embedded microprocessor in their project to reduce the processed data quantity.…”

“…The soil resistivity measurement is essential for forestry and precision agriculture applications. Shinghal et al 15 measure the soil moisture content to help farmers in adapting activities to achieve optimum agricultural production. Soil resistivity detection may help in monitoring earthing operations and also correlate with soil physical properties as cohesion and plasticity.…”

Environmental Technology Platform Architecture for In Situ Monitoring Forest Areas of Amazonian region – A case study in Maiandeua Island, Brazil

“…It is a non-cumulative and dimensionless index, when the index value is less than 2.5, then there is a risk of fire, that is, the day will be an opportune time for occurrence of forest fires (see table 1). In other studies, with research related to monitoring in-situ there is concern with the simulation and sensor networks for forests or rural areas [14], while others are concerned with new mathematical or computational models of thermal comfort in rural or anthropogenic areas [15]. While the study in this paper proposes an architecture of a BRASSEN that supports environmental extreme cases, such as understorey fires.…”

Identification of the Type of Agriculture Suited for Application of Wireless Sensor Networks

“…For example, the traditional humidity sensors utilized in agriculture have a downside that they acquire a large amount of data which is to be processed or transmitted. Whereas the intelligent sensor by Shinghal et al (2011) uses a traditional sensor and an embedded processor that processes the acquired data using algorithms to reduce the amount of data collected. Subsequently only relevant information is extracted and then presented in a format minimizing post-processing latency.…”