Abstract
Crop monitoring and harvesting by ground robots in steep slope vineyards is an intrinsically complex challenge, due to two main reasons: harsh conditions of the terrain and reduced time availability and unstable localization accuracy of the Global Positioning System (GPS). In this paper the use of agricultural wireless sensors as artificial landmarks for robot localization is explored. The Received Signal Strength Indication (RSSI), of Bluetooth (BT) based sensors/technology, has been characterized for distance estimation. Based on this characterization, a mapping procedure based on Histogram Mapping concept was evaluated. The results allow us to conclude that agricultural wireless sensors can be used to support the robot localization procedures in critical moments (GPS blockage) and to create redundant localization information.

Abstract

Abstract
Animal experiments have gained importance in human diseases studies, namely neurological diseases and its biomechanical and physiological aspects. As a model of human disease, the rat offers many advantages over other organisms. For the biomechanical aspects of locomotion these studies are based on the analysis of animals' kinetic parameters, accessed through a locomotion measurement system. However, these systems are not yet thoroughly developed, are still scarce and are also very expensive when developed for studies using small rodents. In this paper, a system capable of measuring contact forces of small rodents is presented. The platform hardware is based on a 5 x 3 matrix of ultra-sensitive force sensors that produce a set of signals acquired in a LabVIEW (TM) environment, used for data acquisition and processing. The post processing steps include the removal of null data, curve normalization related to the rat's weight and expressed as percentage of passage, resulting in a gait pattern. The proposed cost-effective system has achieved excellent results regarding the locomotion profile of healthy animals.

Abstract
Precision viticulture (PV) and precision agriculture (PA) requires the acquisition and processing of a vast collection of data coming typically from large scale and heterogeneous sensor networks. Unfortunately, sensor integration is far from being simple due to the number of incompatible network specifications and platforms. The adoption of a common, standard communication interface would allow the engineer to abstract the relation between the sensor and the network. This would reduce the development efforts and emerge as an important step towards the adoption of "plug-and-play" technology in PA/PV sensor networks. This paper explores this need and introduces a framework for smart data acquisition in PA/PV that relies on the IEEE 1451 family of standards, which addresses the transducer-to-network interoperability issues. The framework includes a ZigBee end device (sMPWiNodeZ),,as an IEEE 1451 WTIM (Wireless Transducer Interface Module), and an IEEE 1451 NCAP (Network Capable Application Processor) that acts as gateway to an information service provider and WSN (Wireless Sensor Network) coordinator. The paper discusses the proposed IEEE 1451 system architecture and its benefits in PA/PV and closes with results/lessons learned from in-field trials towards smarter WSN.

Abstract
Electrical power quality (PQ) is a crucial competitive and developing factor to all economic activities. The economic impact resulting from a bad PQ would be drastic on all consumers. Computers, uninterruptible and switched power supplies (UPS), and fluorescent lamps/tubes are examples of nonlinear loads that have the consumption of a nonsinusoidal current, which cause disturbances in the power supply system (that may be severe or not). This study discusses residential generic power circuitry analysis and simulation, under nonlinear loads, in connection with undergraduate electrical engineering education. It briefly reviews some of the basic techniques, and presents a software tool that has been found to be very useful in the context. The tool has an easy-to-use, friendly interface, and can be used to teach design techniques or as a laboratory support to study the applicability of known methods to real situations. The students can perform simulations with their own data on Microsoft (TM) Windows (R)-based platforms. (c) 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:340-348, 2014; View this article online at ; DOI

Abstract
Traditional imageryprovided, for example, by RGB and/or NIR sensorshas proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors' ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre- and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestrywherein the combination of UAV and hyperspectral sensors plays a center roleis presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processingby isolating the common user from the processes' mathematical complexityseveral available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper's conclusions.