Termites are the most destructive pests and their attacks significantly impact the quality of wooden buildings. Due to their cryptic behavior, it is rarely apparent from visual observation that a termite infestation is active and that wood damage is occurring. Based on the phenomenon of acoustic signals generated by termites when attacking wood, we proposed a practical framework to detect termites nondestructively, i.e., by using the acoustic signals extraction. This method has the pros to maintain the quality of wood products and prevent higher termite attacks. In this work, we inserted 220 subterranean termites into a pine wood for feeding activity and monitored its acoustic signal. The two acoustic features (i.e., energy and entropy) derived from the time domain were used for this study’s analysis. Furthermore, the support vector machine (SVM) algorithm with different kernel functions (i.e., linear, radial basis function, sigmoid and polynomial) were employed to recognize the termites’ acoustic signal. In addition, the area under a receiver operating characteristic curve (AUC) was also adopted to analyze and improve the performance results. Based on the numerical analysis, the SVM with polynomial kernel function achieves the best classification accuracy of 0.9188.

A Comparison Study of Kernel Functions in the Support Vector Machine and Its Application for Termite Detection

Many species of insect pests can be detected and monitored automatically. Several systems have been designed in order to improve integrated pest management (IPM) in the context of precision agriculture. Automatic detection traps have been developed for many important pests. These techniques and new technologies are very promising for the early detection and monitoring of aggressive and quarantine pests. The aim of the present paper is to review the techniques and scientific state of the art of the use of sensors for automatic detection and monitoring of insect pests. The paper focuses on the methods for identification of pests based in infrared sensors, audio sensors and image-based classification, presenting the different systems available, examples of applications and recent developments, including machine learning and Internet of Things. Future trends of automatic traps and decision support systems are also discussed.

https://www.mdpi.com/2077-0472/10/5/161/pdf

Automatic Detection and Monitoring of Insect Pests—A Review

to reduced costs and environmental impact. Because the practise provides record trail, enhanced traceability of farm activities can be obtained that consumers and administration increasingly require (Stafford, 2000; Bellon-Maurel et al., 2014). PA is a cyclic system. The steps can be divided into data collection and localisation, data analysis, management decisions on applications, evaluation of management decisions; and then a new cycle starts. Each year, data are stored in a database and are used as historical data for future decisionmaking (Fountas et al., 2006; Gebbers and Adamchuk, 2010). All this large amount of potentially spatio-temporal data gathered using PA applications is leading to the ‘big data’ concept that will require optimized algorithms to extract the hidden knowledge and relations among variables. Modern PA has a rather short history. Its application started over the last twenty-five years, when global positioning systems (GPS) and yield monitors were made available in field crops. Harvesting was mechanised and sensors were placed on harvesting machines to measure the spatial distribution of yield continuously. Applications started in cereals using impact or γ-ray grain flow sensors. When first yield monitors were developed and yield maps were created, it was shown that yield and soil properties varied highly within the field. This fact marked the development of modern PA (Hedley, 2015). However, applications in fruit and vegetables German Society for Horticultural Science

https://scholar.ptuk.edu.ps/bitstream/123456789/92/2/81_2_2.pdf

Applications of precision agriculture in horticultural crops

The materials used in the study consisted of 720 small clear specimens of nominal dimensions 20 x 20 x 60 mm, of Turkish Red Pine (Pinus brutia) Lebanon cedar (Cedrus libani), Oriental beech (Fagus oriantalis), and English oak (Quercus robur ) from Turkey. The specimens were grouped into 4 batches of 15 specimens each and were tested in the ETH laboratories in Zurich, Switzerland. The influence of EMC was studied over four batches of 15 specimens each, conditioned for 6-8 weeks before testing at a temperature of 20 ± 2oC and at four different relative humidities (50%, 65%, 85%, and 95%). Time of flight value was measured with an ultrasonic commercial device Steinkamp BP-V. Measurements were made end to end directions (L, R, T) on each specimen, with a constant sensor coupling pressure. According to the time results of ultrasound devices, the wave velocities (length/time) and Edyn were calculated. Samples were also tested in uniaxial compression in order to determine E values in three orthotropic directions using a Zwick Z 100 universal testing machine. A load cell with 100-kN maximum capacity was used for compression tests performed in all directions. The feed rate was defined in such a way that the failure of the specimen should be reached in 90 (±30) s. The strains were evaluated using the digital image correlation DIC technique. Wood MC was determined by the oven-drying method. The R values between E and Edyn ranged from 0.79 to 0.96 for the species tested. Moisture content seems to be an influencing factor on sound velocities.

Proceedings: 19th International Nondestructive Testing and Evaluation of Wood Symposium

Red palm weevil (RPW) poses a serious threat to the cultivation of date palms. It is considered to be the most destructive epidemic pest of palms, responsible for massive economic losses worldwide. Curative methods for RPW are not difficult to apply; however, the early detection of the pest remains a great challenge. Although several detection techniques have been implemented for the early detection of RPW, none of these methods have been proven to be reliable. Here, we use an optical-fiber-distributed acoustic sensor (DAS) as a paradigm shift technology for the early detection of RPW. Our sensitive sensor shows a detection of feeding sound produced by larvae as young as 12 days, in an infested tree. In comparison with existing, commonly-used technologies, this novel sensing technique represents a cost-effective and non-invasive alternative that could provide 24-7, real-time monitoring of 1,000 palm trees or even more. It could also monitor the temperature, an essential feature to control farm fires, another major problem for the cultivation of palm trees around the world.

/pdf/early-detection-of-red-palm-weevil-using-distributed-optical-3yn7sgyfzk.pdf

Early detection of red palm weevil using distributed optical sensor.

During the last two decades Red Palm Weevil (RPW, Rynchophorus Ferrugineus) has become one of the most dangerous threats to palm trees in many parts of the World. Its early detection is difficult, since palm trees do not show visual evidence of infection until it is too late for them to recover. For this reason the development of efficient early detection mechanisms is a critical element of RPW pest management systems. One of the early detection mechanisms proposed in the literature is based on acoustic monitoring, as the activity of RPW larvae inside the palm trunk is audible for human operators under acceptable environmental noise levels (rural areas, night periods, etc.). In this work we propose the design of an autonomous bioacoustic sensor that can be installed in every palm tree under study and is able to analyze the captured audio signal during large periods of time. The results of the audio analysis would be reported wirelessly to a control station, to be subsequently processed and conveniently stored. That control station is to be accessible via the Internet. It is programmed to send warning messages when predefined alarm thresholds are reached, thereby allowing supervisors to check on-line the status and evolution of the palm tree orchards. We have developed a bioacoustic sensor prototype and performed an extensive set of experiments to measure its detection capability, achieving average detection rates over 90%.

https://www.mdpi.com/1424-8220/13/2/1706/pdf

On the Design of a Bioacoustic Sensor for the Early Detection of the Red Palm Weevil

En este articulo se pretende recoger la experiencia realizada en la asignatura "Sistemas Operativos" de segundo curso de Ingenieria Tecnica en Informatica de Gestion, impartida en la Escuela Politecnica Superior de Orihuela de la Universidad Miguel Hernandez. En concreto la experiencia se ha realizado sobre la parte del temario de la asignatura que cubre los conceptos de concurrencia, exclusion mutua y sincronizacion de procesos. La utilizacion de las nuevas tecnologias no garantiza unos mejores resultados en el aprendizaje de los alumnos. Lo que si desempena un papel crucial en la obtencion de buenos resultados es, especialmente, la forma en la que la tecnologia es puesta en practica y utilizada [9]. Con este ejemplo proponemos una metodologia para la inclusion de las nuevas tecnologias en el aula cuyos objetivos principales son intentar garantizar un buen rendimiento en las practicas de la asignatura asi como obtener una mayor motivacion del alumnado, una mejor comprension de los conceptos teoricos y un uso planificado y guiado en el proceso de ensenanza-aprendizaje. Para construir dichos objetivos se ha puesto en marcha, siguiendo la planificacion de dicha metodologia, el uso en el aula de una herramienta que simula el efecto de los semaforos, los monitores y la sincronizacion de procesos llamad BACI (Ben-Ari Concurrent Interpreter) [1]

Docencia de semáforos y monitores con BACI: un ejemplo de aprendizaje guiado

In this work we propose several parallel algorithms to compute the twodimensional discrete wavelet transform (2D-DWT), exploiting the available hardware resources. In particular, we will explore OpenMP optimized versions of 2DDWT over a multicore platform and we will also develop CUDA-based 2D-DWT algorithms which are able to run on GPUs (Graphics Processing Unit). The proposed algorithms are based on several 2D-DWT computation approaches as (1) filter-bank convolution, (2) lifting transform and (3) matrix convolution, so we can determine which of them better adapts to our parallel versions. All proposed algorithms are based on the Daubechies 9/7 filter which is widely used in image/video compression.

Héctor Migallón Gomis

Papers

On the Design of a Bioacoustic Sensor for the Early Detection of the Red Palm Weevil

Docencia de semáforos y monitores con BACI: un ejemplo de aprendizaje guiado

Speeding-up the discrete wavelet transform computation with multicore and GPU-based algorithms