A heuristic optimization algorithm for adaptive wireless sensor network design and energy management for precision agriculture is presented. The algorithm takes into account application-specific requirements, communication constraints and energy conservation characteristics. Genetic algorithms are used as the optimization tool of the developed system and an appropriate fitness function is devel...

The objective of this paper was to report the development of precision agriculture for rice crop production in Taiwan during past five years. Three multi-disciplinary research teams have been organized for the purposes of developing techniques required for monitoring growth status and environmental conditions for rice crop; integrating the elements necessary for fertilization recommendation sys...

This paper gives a state-of-art of wireless sensor network (WSN) technologies and solutions applied to precision agriculture (PA). The paper first considers applications and existing experiences that show how WSN technologies have been introduced in to agricultural applications. Then, a survey in hardware and software solutions is related with special emphasis on technological aspects. Finally,...

Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on...

This paper gives an outline of key technologies necessary for science-based agriculture. In order to design future agriculture, present agriculture should be redesigned based on the context of smart agriculture that indicates the overall form of agriculture including a social system while the present precision agriculture shows a technical form of agriculture only. Wireless Sensor Network (WSN)...

Using the Wireless Sensor Networks WSNs in a wide variety of applications is currently considered one of the most challenging solutions. For instance, this technology has evolved the agriculture field, with the precision agriculture challenge. In fact, the cost of sensors and communication infrastructure continuously trend down as long as the technological advances. So, more growers dare to imp...

In this paper, we propose several techniques for data reduction and spatialtemporal prediction in precision agriculture databases. The proposed methods are based on various statistical and machine learning techniques including sensitivity based analysis, spatial-temporal autoregression, multiple time series and response modeling with spatially-correlated residuals. The considered techniques are...

Precision Agriculture intersection of computer science and agriculture from large-scale, uniform treatment to small-scale, precise treatment large data collections one of the first steps in data mining: visualise the data Visualisation visualise data components use self-organising maps use Sammon's Mapping find hidden correlations recover data interdependencies → gain insights into data sets Da...

The LISA (Low-Input Sustainable Agriculture) program was launched to reduce the use of off-farm inputs with the greatest potential to harm the environment or the health of farmers and consumers. This is one of the operational definitions of sustainable agriculture. However, LISA has not gained appreciable support from the agricultural sector, since the nature of LISA decreases profits. On the o...