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A 3D schema of the enclosure with : (a) image sensor (camera), (b) CM3000 node telosb compatible, (c) batteries.
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This article shows the implementation of a wireless image-sensor node capable of taking images of plagues that attack fruits crops. Images can be transmitted over a wireless sensor network in order to build the plague population database and to take appropriate countermeasures in case of infection. Wireless sensor networks are suitable to implement...
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Citations
... In Gonzalez et al. (2014), the authors shows the implementation of a wireless image-sensor node capable of taking images of plagues that attack fruits crops. Images can be transmitted over a wireless sensor network in order to build the plague population database and to take appropriate countermeasures in case of infection. ...
The problem of image retrieval in wireless sensor networks has been well studied. Towards image retrieval in WSN, various methods have been discussed earlier, but suffer to achieve higher performance in image mining. To improve the performance, an efficient QoS adaptive image mining technique has been presented in this paper. The method focused on the efficiency in image mining as well as achieving QoS in WSN. The image has been processed to remove the noise by applying Gabor filters. From the noise removed image, the local binary pattern has been generated at each region of the image to produce regional local binary pattern (RLBP). The RLBP feature extracted has been used to measure the similarity between various images. The method maintains in the taxonomy of various image classes, and each class has different features. The input query has been measured for its similarity towards various classes from taxonomy. According to the similarity a single class has been identified. Based on the class identified, a subset of nodes from WSN has been identified where the relevant Images are available. To reach the data nodes the method identifies the list of routes and estimates traffic bandwidth latency (TBL) support. Based on the value of TBL support a specific route has been selected to perform image retrieval. The RLBP feature generated has been transferred to the data nodes, where the method estimates RLBPS (RLBP similarity). According to the value of RLBP similarity, subsets of images have been selected and transmitted the source node. The method improves the performance of image mining in WSN with less complexity.
... With the development of modern sensors and sensing technology, field information collection in precision agriculture could be achieved by a multiplicity of technologies, including wireless network sensors (WSNs), remote sensing (RS), global positioning system (GPS), and geographic information system (GIS). Among them, for the low-cost and low-energy consumption sensor nodes deployment, the WSNs has been widely used in agriculture for automated irrigation management [14], fertilization [15,16], pesticide detection and control [17,18], as well as environment monitoring and greenhouses controlling [19]. On the other hand, RS coupled with GPS-coordinates as a promising data collection tool has shown great potential in maps and models generation of the soil and crop properties in large field and has been widely used for many decades to estimate spatial and temporal crop factors and soil variability, to provide guidance for weed control and fertilizer management etc., and to discover the certain type of crop stress and predict relative crop yields [20,21]. ...
Timely identifying and quantifying significant spatial and temporal variability in agricultural field has been a crucial factor for improving agricultural production and management. This paper focuses on the mainstream techniques and applications can be adopted to improve the field information collection method. In this paper, the development of wireless sensor networks (WSNs) and remote sensing (RS) technology were reviewed, especially the micro unmanned aerial vehicle (mUAV)-based WSNs and mUAV-based RS by analyzing its applications in field information collection, and pointed out its existing benefits and limitations. A system encompassed multiple technique approaches was proposed in this paper which is called air-ground multi-sensor monitoring system. With the diversification methods of in-field information collection and the improvement of detection precision, an in-field information collection system will play an important role in controlling the farming operations of mechanized agriculture and optimizing the management of agricultural machinery group. In the future, the combination of mUAV, WSNs and RS for crop and soil monitoring will become a powerful tool to obtain field information, increase production, optimize the overall farming practices and input of resources and provide comprehensive reference for the study of soil-crops-machine relationships.
... Wireless Visual Sensor Network (WVSN) is a platform in a communication system that consists of small visual sensor nodes in the form of a camera with an embedded processor and the ability to communicate wirelessly [1][2][3][4][22][23]. The main difference of WVSN from other sensor networks is its ability to transfer visual data such as images or videos. ...
Wireless Visual Sensor Network (WVSN) is a system that consists of visual sensor nodes with an embedded processor. WVSN devices have limited resources of energy, computation capability, memory, and bandwidth. Due to these limitations theimplementation of WVSN for large multimedia data, such as images, become a challenging task. Therefore, it is requiredcompressed images prior to transmission. In addition to the limited resources, the system implementation strongly affects theefficiency of the working system. The main contribution of this research is to offer a technicalsolution of simpler image compression on the WVSN platform. JPEG 2000 is investigated as an alternative compression methodto reduce the size of data transfer on WVSN using Embedded Linux as its operating system. Compressed images are transferredto a receiver on communication of IEEE 802.15.4.. This paper shows that the energy consumption for compression andtransmission will reduce to only 10.48%, 13.60%, and 17.11% compared to raw image. BER will significantly reduce byimplementing image compression. Therefore, it is demonstrated that this model significantly increases energy efficiency, memoryutilization efficiency, and data transfer time with acceptable PSNR, compared to uncompressed images.
An intelligent cultivation management system is proposed. In the system, by using ZigBee wireless sensor network monitoring the temperature, humidity, light, the concentration of CO2, and other environmental factors based on solar power supply. Thus small gardens crop growth conditions are obtained. Through wireless sensor network, the irrigation and fertilization for small gardens crop growth are controlled by management end software, which aims at remote wireless elaborating intelligent management, so the economic benefit is improve.
Electric potential (EP) signals are produced in plants through intracellular processes, in response to external stimuli (e.g., watering, mechanical stress, light, and acquisition of nutrients). However, wireless transmission of a massive amount of biologic EP signals (from one or multiple plants) is hindered by existing battery-operated wireless technology and increased associated monetary cost. In this paper, a self-powered batteryless EP wireless sensor is presented that harvests near-maximum energy from the plant itself and transmits the EP signal tens of meters away with a single switch, based on inherently low-cost and low-power bistatic scatter radio principles. The experimental results confirm the ability of the proposed wireless plant sensor to achieve a fully autonomous operation by harvesting the energy generated by the plant itself. In addition, EP signals experimentally acquired by the proposed wireless sensor from multiple plants have been processed using nonnegative matrix factorization, demonstrating a strong correlation with environmental light irradiation intensity and plant watering. The proposed low-cost batteryless plant-as-sensor-and-battery instrumentation approach is a first but solid step toward large-scale electrophysiology studies of important socioeconomic impact in ecology, plant biology, and precision agriculture.
