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The early detection of pests is key for the maintenance of high-value masterpieces and historical buildings made of wood. In this work, we the present detailed design of an ultra-low power sensor device that permits the continuous monitoring of the presence of termites and other xylophagous insects. The operating principle of the sensor is based on...
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... provide a rough estimation of a battery-powered design using this technique, Table 3 shows the estimated maximum battery life for different battery models. The results in Table 2 show excellent sensor lifespans, allowing the node to survive for a long time without requiring maintenance. ...
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This research evaluates and characterizes the acoustic emission activity generated by Reticulitermes termites as recorded by piezoelectric sensors with sensitivity in the ultrasound range (greater than 20 kHz). To this end, the acoustic emission activity was recorded under controlled conditions of temperature and moisture content in three pine wood...
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... It is just because of the services and capabilities offered by the internet of things. Most authors have reviewed that most IoT architectures consist of four layers, the perception/sensors or device layer, the transport/network layer, which includes protocols, the processing or services layer, which offers processing and analysis of data and the application layer in last which includes monitoring and control applications [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]. These layers include all the main components of any IoT solution. ...
... Open issues and challenges were discussed, and IoT integration with the cloud was also discussed. Some surveys are available, but in [35], different types of surveys have been surveyed, and they have been categorized according to time. In the early days of the survey, communication protocols and communication technologies were discussed, while later, the architecture of IoT was explained, while the best applications were mentioned in the last round of surveys. ...
... If we compare the use of IoT in agriculture [20,21,25,26,[31][32][33][34][35]38,39], we will see that researchers have conducted great work and tried to improve agricltural operations using various latest technologies. Some researchers are detecting the presence of pests based on weather parameters. ...
IoT technology and drones are indeed a step towards modernization. Everything from field monitoring to pest identification is being conducted through these technologies. In this paper, we consider the issue of smart pest detection and management of cotton plants which is an important crop for an agricultural country. We proposed an IoT framework to detect insects through motion detection sensors and then receive an automatic response using drones based targeted spray. In our proposed method, we also explored the use of drones to improve field surveillance and then proposed a predictive algorithm for a pest detection response system using a decision-making theory. To validate the working behavior of our framework, we have included the simulation results of the tested scenarios in the cup-carbon IoT simulator. The purpose of our work is to modernize pest management so that farmers can not only attain higher profits but can also increase the quantity and quality of their crops.
... The deployment of efficient wireless sensor nodes in cultural heritage contexts is not straightforward [36][37][38][39][40][41][42][43]. Sensor nodes use radiofrequency (RF) to transmit information that has to travel relatively long distances and/or pass through thick walls, moreover, the energy requirements must be kept low to give the nodes a long life-span. ...
... SubGHz bands seems the best option for these scenarios as we demontrated in a previous research [43] where we designed an ultra-low power sensor node appropriate for heritage building monitoring. This node was initially designed for monitoring the equilibrium moisture content in wood and the detection of termites [39]. ...
The effective implementation of preventive conservation strategies requires tools to continuously measure the environmental conditions to which the cultural objects are exposed. In this sense, the European Horizon 2020 project CollectionCare aims to provide an affordable preventive conservation service for individual objects focused to small museums with limited budgets. Although the use of data loggers has been a must in the past, new deployments tend to use wired and wireless sensors that provide real-time information and the ability to instantly analyse the data, allowing immediate action to be taken in the event of a threat towards a cultural object. For already constructed buildings, wireless systems have the advantage that, a priori, deployments are simpler, faster and cheaper, but have to deal with complex heritage environments with long distances to be covered and very thick walls to cross. In many cases, commercial systems of this type are not economically viable for small museums with limited budgets. Moreover, conservators who try to approach such solutions are often overwhelmed by unclear technical specifications that do not allow them to determine whether the solution fits their environment or not, giving rise to great frustration. Among others, the CollectionCare includes the design of a specific low-cost wireless sensor, being the aim of this article to present to both technical and non-technical readers, the design choices made regarding the housing, attachment method, power source, wireless transmission technique and selection of the environmental sensors following European standards. Also, the effective implementation of the device in three stages to prove the concep until to get a near-production version is presented. The developed device has been deployed in museums in Belgium, Italy, Greece, Latvia, Denmark and Spain, and the validation results are presented, showing that it is feasible to have a cost-effective proposal that it is easy to install and configure and can operate for 10 years without the need for maintenance or battery replacement except if it is needed to comply with annual recalibration if standards such as ISO 11799:2015 are required.
... While these camera-based smart traps are effective at automating trap inspections, the high computational complexity and power consumption associated with transmitting and processing images have limited the scale at which they can be deployed effectively. This issue only compounds as image resolution and upload frequency increase, resulting in the need for solar panels, large batteries and associated infrastructure to accompany each trap [14]. Other research teams have focused on optoelectronic beam break type sensors as a simple, low-power, low-cost sensing solution [15]. ...
... Sustainability 2022, 14, 9577 Acknowledgments: We thank the FarmSense Inc. team, especially Shailendra Singh and Eamonn Keogh for sharing their original prototype with us and discussing improvements for biosecurity purposes. The present authors do not claim any IP on the current smart sensor trap which is different from those commercialised by FarmSense Inc. ...
Several lepidopterans are pests in horticulture and pose biosecurity risks to trading countries worldwide. Efficient species-specific semiochemical lures are available for some of these pests, facilitating the implementation of surveillance programmes via trapping networks. These networks have a long history of success in detecting incursions of invasive species; however, their reliance on manual trap inspections makes these surveillance programmes expensive to run. Novel smart traps integrating sensor technology are being developed to detect insects automatically but are so far limited to expensive camera-based sensors or optoelectronic sensors for fast-moving insects. Here, we present the development of an optoelectronic sensor adapted to a delta-type trap to record the low wing-beat frequencies of Lepidoptera, and remotely send real-time digital detection via wireless communication. These new smart traps, combined with machine-learning algorithms, can further facilitate diagnostics via species identification through biometrics. Our laboratory and field trials have shown that moths flying in/out of the trap can be detected automatically before visual trap catch, thus improving early detection. The deployment of smart sensor traps for biosecurity will significantly reduce the cost of labour by directing trap visits to the locations of insect detection, thereby supporting a sustainable and low-carbon surveillance system.
... Data are transferred wirelessly to the gateway using the 868 MHz European unlicensed industrial, scientific, medical (ISM) band, Gaussian frequency-shift keying (GFSK) for the modulation, and a fixed transmission frequency for all the sensor nodes. This sensor node is an adaptation of a previous one devoted to the detection of xylophagous [53] that copes adequately with the requirements of lifespan and long distances and tick walls of historical buildings. The wireless sensor nodes, depicted in Figure 2a, are built around an ultra-low power C8051F920 microcontroller (Silicon Laboratories Inc., San José, CA, USA), a SHT15 temperature and humidity sensor (Sensirion, Staefa ZH, Switzerland) with a typical accuracy of 0.3 • C, a CC1101 radio modem (Texas Instruments, DA, USA), and a high-density 3.6 V, 1 Ah Lithium-thionyl battery. ...
... Data are transferred wirelessly to the gateway using the 868 MHz European unlicensed industrial, scientific, medical (ISM) band, Gaussian frequencyshift keying (GFSK) for the modulation, and a fixed transmission frequency for all the sensor nodes. This sensor node is an adaptation of a previous one devoted to the detection of xylophagous [53] that copes adequately with the requirements of lifespan and long distances and tick walls of historical buildings. The gateway, shown in Figure 2b, was built to be as flexible as possible in order to experiment with different approaches, so it was decided to implement it around a Raspberry Pi 3 board (Broadcom Inc., San Jose, CA, USA) and the Linux operating systems. ...
... The difference between Tmean of UP4 and EN1 is 0.61 °C, which is consistent with the accuracy of the Sensirion SHT15 (±0.3 °C) in the range of temperatures used for the calibration. In this design, it was decided to select the most accurate model of the SHT1x series, in contrast to previous projects [53] where Sensirion SHT10 was utilized to optimize the cost of the solution. Currently, Sensirion SHT1x series are currently deprecated, based The difference between T mean of UP4 and EN1 is 0.61 • C, which is consistent with the accuracy of the Sensirion SHT15 (±0.3 • C) in the range of temperatures used for the calibration. ...
Adequate thermic conditions are required for the preventive conservation of artworks, but such optimum conditions cannot always be achieved in historical buildings such as ancient churches. In those cases, it is of interest to assess the potential risk of punctual changes in indoor environments that can be harmful to artworks. These conditions can be assessed by means of a microclimate monitoring system comprised of a set of energy-efficient wireless sensors connected to the cloud using IoT techniques. This approach was followed at the baroque church of Saint Thomas and Saint Philip Neri in Valencia (Spain). A set of 26 wireless nodes was installed, which recorded values of temperature and relative humidity every hour for a period of 7 months. Small differences of temperature were obtained among sensors, so that an efficient methodology based on principal component analysis (PCA) was applied for the characterization of similarities and dissimilarities between sensors. Daily ranges of temperatures were studied as well as mean trajectories, differences between days of the week, and changes in the correlation structure of daily median values over time. Results provide a framework for an efficient characterization of temperatures in heritage buildings based on a network of wireless sensors. Such a framework is useful to assess the potential risk of temperature fluctuations on the preventive conservation of historical buildings and artworks.
... This sensor node is an adaptation of a previous one devoted to the detection of xylophagous [58] and copes adequately with the requirements of life-span and long distances and thick walls of historical buildings [1]. ...
The baroque church of Saint Thomas and Saint Philip Neri (Valencia, Spain), which was built between 1727 and 1736, contains valuable paintings by renowned Spanish artists. Due to the considerable height of the central nave, the church can experience vertical temperature gradients. In order to investigate this issue, temperatures were recorded between August 2017 and February 2018 from a wireless monitoring system composed of 21 sensor nodes, which were located at different heights in the church from 2 to 13 m from the floor level. For characterizing the temperature at high, medium and low altitude heights, a novel methodology is proposed based on sparse Partial Least Squares regression (sPLS), Linear Discriminant Analysis (LDA), and the Holt-Winters method, among others, which were applied to a time series of temperature. This approach is helpful to discriminate temperature profiles according to sensor height. Once the vertical thermal gradients for each month were characterized, it was found that temperature reached the maximum correlation with sensor height in the period between August 10th and September 9th. Furthermore, the most important features from the time series that explain this correlation are the mean temperature and the mean of moving range. In the period mentioned, the vertical thermal gradient was estimated to be about 0.043 ∘C/m, which implies a difference of 0.47 ∘C on average between sensor nodes at 2 m from the floor with respect to the upper ones located at 13 m from the floor level. The gradient was estimated as the slope from a linear regression model using height and hourly mean temperature as the predictor and response, respectively. This gradient is consistent with similar reported studies. The fact that such gradient was only found in one month suggests that the mechanisms of dust deposition on walls involved in vertical thermal gradients are not important in this case regarding the preventive conservation of artworks. Furthermore, the methodology proposed here was useful to discriminate the time series at high, medium and low altitude levels. This approach can be useful when a set of sensors is installed for microclimate monitoring in churches, cathedrals, and other historical buildings, at different levels and positions.
... Others describe effects of temperature on rates of activity [60]. Others incorporate optical sensors in traps [150,275] with similarities to pitfall traps used for monitoring stored product insects [236]. ...
... Others describe effects of temperature on rates of activity [60]. Others incorporate optical sensors in traps [150,275] with similarities to pitfall traps used for monitoring stored product insects [236]. Finally, we note the increased usage of acoustic detection methods against invasive stored product pests, e.g., Trogoderma inclusum LeConte [276] and other invasive Trogoderma spp. ...
Acoustic technology provides information difficult to obtain about stored insect behavior, physiology, abundance, and distribution. For example, acoustic detection of immature insects feeding hidden within grain is helpful for accurate monitoring because they can be more abundant than adults and be present in samples without adults. Modern engineering and acoustics have been incorporated into decision support systems for stored product insect management, but with somewhat limited use due to device costs and the skills needed to interpret the data collected. However, inexpensive modern tools may facilitate further incorporation of acoustic technology into the mainstream of pest management and precision agriculture. One such system was tested herein to describe Sitophilus oryzae (Coleoptera: Curculionidae) adult and larval movement and feeding in stored grain. Development of improved methods to identify sounds of targeted pest insects, distinguishing them from each other and from background noise, is an active area of current research. The most powerful of the new methods may be machine learning. The methods have different strengths and weaknesses depending on the types of background noise and the signal characteristic of target insect sounds. It is likely that they will facilitate automation of detection and decrease costs of managing stored product insects in the future.
... There is a wide bibliography [4] on optical [5,6], laser vibrometry [7], piezoelectric sensors, and accelerometers [8][9][10][11], used to detect locomotion and feeding sound of larvae or adult pests inside the tree trunk. A mildly intrusive and widely applied method for inspection of commodities is based on inserting a piezoelectric probe in the tree trunk to listen for potential internal audio activity due to feeding and locomotion (i.e., passive acoustic detection) [12][13][14][15][16][17][18][19]. ...
Is there a wood-feeding insect inside a tree or wooden structure? We investigate several ways of how deep learning approaches can massively scan recordings of vibrations stemming from probed trees to infer their infestation state with wood-boring insects that feed and move inside wood. The recordings come from remotely controlled devices that sample the internal soundscape of trees on a 24/7 basis and wirelessly transmit brief recordings of the registered vibrations to a cloud server. We discuss the different sources of vibrations that can be picked up from trees in urban environments and how deep learning methods can focus on those originating from borers. Our goal is to match the problem of the accelerated—due to global trade and climate change— establishment of invasive xylophagus insects by increasing the capacity of inspection agencies. We aim at introducing permanent, cost-effective, automatic monitoring of trees based on deep learning techniques, in commodity entry points as well as in wild, urban and cultivated areas in order to effect large-scale, sustainable pest-risk analysis and management of wood boring insects such as those from the Cerambycidae family (longhorn beetles).
... Optical techniques have also been used to detect termite infestations, based on the variations of reflected light induced by the presence of these insects [119,120]. The developed pest sensors comprised a light emitter (LED) and a receiver (light sensor), positioned inside a small tube, which is then inserted in a wood element, and through which the termites should eventually pass. ...
Significant developments in structural health monitoring (SHM) and in non-destructive testing (NDT) and damage identification techniques for structural timber elements have led to an increasing interest in the application of these technologies. However, specific aspects of timber structures (anisotropy, moisture dependency, high variability), the wide range and novelty of available systems, and the need to adapt them for each configuration, makes specifying and implementing a SHM system a non-trivial task, heavily dependent on previous experience. This article presents a comprehensive review of available SHM and NDT methods, case studies, and a survey on the implementation of SHM in timber structures.
... Wood-boring insects such as termites, weevils and certain beetles can directly affect the health and growth of specific tree species. There is a wide bibliography on piezoelectric sensors, microphones, accelerometers, laser vibrometry and optical methods [1,8,9] used to detect locomotion and feeding sound of larvae or adult pests inside the tree trunk. One should note that all these methods are currently applied manually. ...
This work introduces a device for long term systematic monitoring of trees against borers. A widely applied way to detect wood-boring insects is to insert a piezoelectric probe with an uncoated waveguide in the tree trunk and listen for locomotion or feeding sounds through headphones. This approach has several shortcomings: (a) frequent manual inspection of trees is costly and impractical to scale to hundreds or thousands of trees, (b) the larvae could be present but inactive during the inspection time and, (c) when the trees are in urban environments the background noise can be significant and can mask the feeble sounds of wood-boring insects even with the use of specialized headphones. We introduce a remotely controlled device that records and wirelessly transmits on a scheduled basis short recordings of the internal vibrations of a tree to a server. The user can listen remotely or process the recording automatically to infer the infestation state of the tree with wood-boring insects that feed or move inside the tree. When integrated within the IoT framework this device can scale up to automatically monitoring the trees of the entire city. The proposed approach led to detection results in field trials of the pests Xylotrechus chinensis (Chevrolat) (Cerambycidae) and Rhynchophorus ferrugineus Olivier (Coleoptera: Curculionidae).
... Wood-boring insects such as termites, weevils and beetles can directly affect the health and growth of specific tree species. There is a wide bibliography on piezoelectric sensors, microphones, accelerometers, laser vibrometry and optical methods [1,[8][9] used to detect locomotion and feeding sound of larvae or adult pests inside the tree trunk. One should note that all these methods are manually applied. ...
This work introduces a device for long term systematic monitoring of trees against borers. A widely applied way to detect wood-boring insects is to insert a piezoelectric probe with uncoated waveguide in the tree trunk and listen for locomotion or feeding sounds through headphones. This approach has several shortcomings: a) frequent manual inspection of trees is costly and impractical to be scaled to hundreds or thousands of trees, b) the larvae could be present but inactive during the inspection time and, c) when the trees are in urban environments the background noise can be significant and can mask the feeble sounds of wood-boring insects even with the use of specialized headphones. We introduce a remotely controlled device that records and wirelessly transmits on a scheduled basis short recordings of the internal vibrations of a tree to a server. The user can listen remotely or process the recording automatically to infer the infestation state of the tree with wood-boring insects that feed or move inside the tree. When integrated within the IoT framework this device can scale up to automatically monitoring the trees of the entire city. The proposed approach led to detection results in field trials of the pests Xylotrechus chinensis and Rhynchophorus ferrugineus.
