Outdoor Fields Research Articles

Development of a smart IoT‐based drip irrigation system for precision farming

AbstractPrecision irrigation scheduling using real‐time sensors has the potential to boost water use efficiency while maximizing resource utilization. Traditional farming is adversely affected by improper resource management. To overcome a farmer's efforts, an IoT‐based drip irrigation system was developed and tested for system performance. It was compared with an ETc‐based drip irrigation system for brinjal crops grown in planter beds filled with vertisols. The developed system, consisting of sensors and microcontrollers, records the environmental parameters, namely, soil moisture content, soil temperature, and relative humidity and temperature. Irrigation scheduling was programmed using upper (field capacity) and lower thresholds (50% plant available water). Irrigation applications were triggered when the soil moisture value reached the lower threshold (33%) and ended after the field capacity was attained (46%). The information captured by the sensors is wirelessly uploaded to the cloud server using IoT technology, which can be accessed from anywhere in the world. It was observed that the IoT‐based drip irrigation testing plant grew 1.3 cm taller than the ETc‐based drip irrigation testing plant. The length and width of brinjal plant leaves also increased more than the ETc‐based drip irrigation treatments. The IoT‐based drip irrigation treatments improved pump operating time, leaf length and width by 85 min, 4.4 cm and 3.1 cm, respectively, compared to 125 min, 3.7 cm and 2.4 cm for the ETc‐based drip irrigation treatment. During a period of 31 days, water savings of 35% were observed compared to ETc‐based drip irrigation. The developed system was rugged, and a water‐resistant enclosure allowed its use in outdoor agriculture fields.

Photodegradation and Photostability of Bamboo: Recent Advances

Bamboo and its products are widely used in indoor and outdoor fields. Photodegradation occurs easily on the surface when bamboo is exposed to ultraviolet (UV) light from solar radiation. This induces surface discoloration and degrades the physical properties of bamboo, which not only negatively affects its utility and aesthetic characteristics but also restricts its application in outdoor environments. In this work, we review the mechanism of bamboo photodegradation, in which the behavior of lignin is key. The changes in bamboo’s microstructure, surface color, and chemical composition during photodegradation are described in detail. Methods for enhancing its photostability, including the application of transparent coatings containing UV absorbers and hindered amine light stabilizer compounds on bamboo surfaces, are then systematically summarized, and potential approaches to combat the photodegradation of bamboo surfaces are discussed. On the basis of the recent advances of photodegradation and photostability of bamboo, this review provides new insights into the scientific application and protection of bamboo in the outdoor field.

Time build-up properties of the weathering resistant radiophotoluminescence glass (SAPANS)

Time build-up properties of a recently developed radiophotoluminscence (RPL) glass made of silver-activated P2O5–Al2O3–Na2O–Ag2O, named “SAPANS” herewith, were examined using 137Cs source γ-rays. It was observed that the RPL intensities of SAPANS continuously increased at room temperature and did not reach a stable state even at six months after irradiation. For obtaining stable RPL values corresponding to dose levels, preheating at 160 °C for 1 h was judged to be the most suitable. The good weathering resistance of SAPANS was confirmed in a 63-days outdoor weathering test in the summer season; its physical and dosimetric properties were well maintained after the long exposure to the harsh environment. According to these findings, it is expected that SAPANS will be effectively applied to long-term radiation monitoring at various types of working/living places including outdoor fields.

Macro X-ray fluorescence analysis of XVI-XVII century Italian paintings and preliminary test for developing a combined fluorescence apparatus with digital radiography

Using portable instruments for the preservation of artworks in heritage science is more and more common. Among the techniques, Macro X-Ray Fluorescence (MA-XRF) and digital radiography (DR) play a key-role in the field, therefore a number of MA-XRF scanners and radiographic apparatuses have been developed for this scope. Recently, the INFN-CHNet group, the network of the INFN devoted to cultural heritage, has developed a MA-XRF scanner for in-situ analyses. The instrument is fully operative, and it has already been employed in museums, conservation centres and out-door fields. In the present paper, the MA-XRF analysis conducted with the instrument on four Italian artworks undertaking conservation treatments at the conservation centre CCR “La Venaria Reale” are presented. Results on the preliminary test to combine DR with MA-XRF in a single apparatus are also shown.

Values of outdoor fields and orientation for contribution projects to local communities of mountain bikers

Values of outdoor fields and orientation for contribution projects to local communities of mountain bikers

Presence of metals and metalloids in crumb rubber used as infill of worldwide synthetic turf pitches: Exposure and risk assessment

Crumb rubber derived from end-of-life tires (ELTs) is frequently used as infill of synthetic turf pitches, promoting circular economy. Although important to reduce the accumulation of waste, the use of recycled ELTs can be a problem to human health and the environment, both by direct contact during pitch use and by the release of these elements to the surroundings, mostly via volatilization and leaching. The present study aimed to evaluate the distribution of metals in ELT-derived crumb rubber collected in artificial turf worldwide and assess possible trends by country, pitch age and type (indoor vs. outdoor). The concentration ranges observed are very wide, especially in outdoor fields and for the most abundant metals, namely Zn (2989–5246 mg/kg), Fe (196–5194 mg/kg), Mg (188–1795 mg/kg) and Al (159–1882 mg/kg). For Zn, the levels were mostly above the safe limits set in European directives for relatable matrices (soils and toy materials), and the same happened for Pb, a much more toxic metal at lower concentrations. A multi-pathway human exposure study was also performed, and the risk assessment shows non-carcinogenic and carcinogenic risks from accidental crumb rubber ingestion (with Cr and Pb as major contributors) above the acceptable values for all the receptors except adult bystanders, with a higher significance to younger individuals. These results bring a different perspective regarding most of the studies reporting low risks related with exposure to metals in crumb rubber.

Research on Stability of the Four-wheeled Robot for Emergency Obstacle Avoidance on the Slope

Background: In recent years, patents suggest that four-wheeled robots have been widely used in outdoor reconnaissance fields. However, the emergency obstacle avoidance of the four-wheeled robot on the slope is affected by the slope angle and the friction coefficient of the slope, and its motor torque and yaw torque are prone to abrupt changes, causing the four-wheeled robot to slip greatly. According to relevant literature, PID control methods (dual-loop PID control and linear PID control) make the robot control motor current fluctuate greatly during the emergency obstacle avoidance process. Hence, the PID controller of the four-wheeled robot needs to be optimized. Objective: This study aims to establish a novel dual-loop fuzzy PID controller to improve the stability of the four-wheeled robot during emergency obstacle avoidance on the slope. Methods: Establishing the kinematics and dynamics equations of the four-wheeled robot, and determining the speed of the center of mass and the yaw rate are important control parameters for controlling the steering motion of the robot. Aiming at the PID controller of the past four-wheeled robot, its response speed is slow, and the overshoot of the speed of the center of mass and the yaw rate is large. For this reason, the dual-loop fuzzy PID controller is designed. Comparison simulation is carried out by the MATLAB programming. Results: It is concluded that the control effect of the four-wheel robot with the dual-loop fuzzy PID controller is the best. The steering angle and displacement response speed of the four-wheel robot are faster, and there is basically no overshoot. The response of the yaw rate is increased by 30%, the average deviation of the linear motion trajectory is reduced by 41.27%, and the average deviation of the circular steering motion trajectory is reduced by 29.51%. Conclusion: The dual-loop fuzzy PID controller can provide reference for the PID control research of other four-wheeled robots.

Effects of the 2018 Camp Fire on birth outcomes in non-human primates: Case-control study

The November 2018 Camp Fire, a devastating wildfire in Northern California, occurred during the peak of breeding season for field monkeys at the California National Primate Research Center (CNPRC). Effects of environmental stressors, such as wildfires, on birth outcomes in primates, and in humans, are poorly understood. Additionally, wildfires are of growing concern due to their increasing frequency and severity. The objective was to examine the impact of wildfire smoke on fertility, timing of birth, and pregnancy loss for field monkeys.A unique case-control study to investigate birth outcomes in rhesus macaques (Macaca mulatta) was conducted at the CNPRC. All females in the study were maintained in outdoor fields during a period of elevated ambient wildfire smoke from November 8–22, 2018. In addition to ambient air quality evaluations, the effects on fertility, timing to birth, and pregnancy loss were documented. Archival records of approximately 5,000 conceptions from the previous nine years served as control data.During the Camp Fire, ambient fine particulate (PM 2.5) levels exceeded the 24 -h National Ambient Air Quality Standard (35 μg/m 3) of the United States Environmental Protection Agency, reaching levels as high as 185 μg/m 3. A statistically significant association was observed between birth loss and the 2018–2019 CNPRC breeding season. As this wildfire event occurred during various stages of early pregnancy, an association can be inferred between early gestational exposure and increased risk of pregnancy loss.

A basic study on estimating location of sound source by using distributed acoustic measurement network

The sounds from childcare facilities are often a cause of noise problems with neighbors, however since the sound power levels of children's play and other sounds in child-care facilities have not become clear, evaluation methods have not been established, making countermeasures difficult. In order to evaluate the noise, it is necessary to model the location of the sound source and the sound power level. We have been developing a sound source identification system that uses multiple Raspberry Pi-based recording devices to estimate the location of a sound source and sound power levels. By using GPS for time synchronization, the system can be distributed and placed without connecting cables, which is expected to expand the measurement area significantly. As a method of estimation, the arrival time difference is calculated by cross-correlation from the signals input to each recording device, and the sound source location is estimated from the calculated arrival time difference and the location information of the device. The effectiveness of this system was verified in an anechoic room and outdoor fields.

Case Study on the Use of the Leaf-Count Method for Drip Fertigation in Outdoor Cucumber Cultivation in Reconstructed Fields Devastated by a Tsunami

Drip fertigation was tested in fields using a nitrogen fertilization method based on leaf increments, with the aim of increasing the cucumber yield in outdoor fields restored after the tsunami disaster in Rikuzentakata City, Iwate Prefecture, in 2011. The 2016 test site (Takata field) was restored as a paddy field, and there were problems with water retention and gravel contamination. The condition of the 2017 test site (Yonesaki field) was better than that of the 2016 site. The drip fertigation method increased cucumber yield by 93% and 27% in the Takata and Yonesaki fields, respectively, when compared to the yield from fields cultivated conventionally. Drip fertigation enables the constant supply of liquid fertilizer to the rhizosphere, and the easy application prevents the scarcity of fertilizer, especially at later stages of growth. In contrast, a real-time soil diagnosis, using the Dutch 1:2 soil–water extract method, was unsuccessful due to flooding, especially in the Takata field. As the purpose of this method is not to reduce the amount of nitrogen provided, but to increase the yield, and because it is difficult to precisely control the application of fertilizer due to precipitation, we suggest that the real-time soil diagnosis and feedback should be omitted to further simplify fertilizer application.

Applying chemical control to suppress liverwort (Marсhantia polymorpha L.) and other mosses when growing containerized seedlings of pine and spruce

The spread of bryophytes (liverworts and green mosses) on the substrate surface in containers and cassettes poses a significant problem when growing containerized coniferous seedlings. It requires a complex control programme to significantly minimize the negative effect which mosses, in particular Marсhantia polymorpha L., pose to the growth of containerized pine and spruce seedlings. In addition to the preventive and agrotechnical measures, this programme should also involve application of the physiologically active substances. North American and European nurseries have faced this problem for a long time, Russian nurseries have started to experience it only in recent years due to increased output of containerized pine and spruce seedlings grown in greenhouses. In this paper, we assessed the effectiveness of some herbicides for moss control and their selectivity to pine and spruce seedlings of different ages. The following chemicals were applied in the tests: Goal 24% EC (a.i. oxyfluorfen), Stomp 33% EC (a.i. pendimethalin), Velpar 90% SP (a.i. hexazinone), Pledge 25% WP (a.i. flumioxazin), Mogeton 25% WP (a.i. quinoclamine), Granstar 75% WDG (a.i. tribenuron-methyl), Anchor-85 75% WDG (a.i. sulfometuron methyl) as well as cinnamon oil and baking soda. The experiments were conducted in greenhouses and outdoor fields. It was found that the pre-emergent (before the pine and spruce shoots appear) application of Mogeton WP and baking soda in the greenhouse resulted in the effective suppression of green mosses for up to 20 weeks after the treatment, without any signs of injury in seedlings. Under the same conditions, Goal EC, Stomp EC, Pledge WP and their mixtures in different combinations, as well as Velpar SP caused significant damage to pine and spruce seedlings. The post-emergent treatment by Velpar SP, Pledge WP, Mogeton WP, Granstar WDG, Anchor-85 WDG, as well as cinnamon oil and baking soda, provided effective and long-term control of liverwort and green mosses in cassettes without damage to the seedlings. Key words: Marchantia polymorpha L., pine, spruce, efficacy, selectivity

Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.

Pallet Handling System with an Autonomous Forklift for Outdoor Fields

In Japan, the aging and depopulation of its workforce are issues. Therefore, the development of autonomous agricultural robots is required for saving manpower and labor. In this paper, we described an autonomous pallet handling system for forklift, which can automatically unload and convey pallets for harvesting vegetables outdoors. Because of inserting the forks into a narrow pallet hole, accurate pallet posture estimation and accurate control of a forklift and the forks are required. The system can detect the pallet by deep learning based object detection from an image. Based on the results of object detection and measurement by horizontal 3D light detection and ranging (LiDAR), the system accurately estimates a distance as well as horizontal and vertical deviation between the forklift and the pallet in the outside field. The forklift is controlled by sliding mode control (SMC) which is robust to disturbances. Furthermore, the vertical LiDAR scans the pallet for precisely adjusting the height of the fork. The system requires the environment with no or little preparation for the automation process. We confirmed the effectiveness of the system through an experiment. The experiment is assumed that the forklift unloads the pallet from the vehicle as the real task of agriculture. The experimental results indicated the suitability of the system in real agricultural environments.

CFD simulation of natural ventilation of a generic building in various incident wind directions: Comparison of turbulence modelling, evaluation methods, and ventilation mechanisms

Single-sided and cross- ventilation of a cube-shaped building at various incident wind directions were stimulated using computational fluid dynamics (CFD). The simulation used either the Reynolds-averaged Navier-Stokes (RANS) equations in conjunction with a 2-equation turbulence model (Standard k-ε model (SKT), Realizable k-ε model (RLZ), or Renormalization group k-ε model (RNG)), or Large Eddy Simulation (LES) with the Wall-Adapting Local Eddy-viscosity model (WALE). LES showed good agreement with wind tunnel data when modeling indoor and outdoor wind fields; RLZ had slightly better results than SKT and RNG. Two evaluation methods were examined: the integration of opening velocities method under-estimated single-sided ventilation rates but over-estimated cross-ventilation rates; the tracer-gas decay method was more computationally demanding of the two. When the tracer-gas method and LES were used in combination, their estimations were most accurate especially if the ventilation was driven by wind flow fluctuations. RANS and LES predicted steady decreases of 92.5% and 81.8% (single-sided ventilation), and 52.6% and 37.2% (cross-ventilation) in ventilation rate as incident wind direction varies from 0° to 90°. Discrepancies between the RANS and LES predictions of ventilation rates were mainly attributable to their respective turbulence-modeling methods.

Portable, wireless, and effective internet of things-based sensors for precision agriculture

Profitability in production farming depends on making correct and timely operational decisions based on current conditions and historical data. Precision agriculture is a comprehensive system designed to optimize agricultural production by carefully tailoring soil and crop management to correspond to the unique conditions found in each field while maintaining environmental quality. This research paper details the development of a portable and wireless sensor network system to remotely monitor the environmental parameters in an agriculture field and provide field managers with alerts and information regarding current conditions while saving the data in a database for future reference. The data acquisition unit consisting of sensors and microcontroller captures the environmental parameter data such as temperature, humidity, light intensity, and soil moisture content. By utilizing Internet of Things technology, the information captured by the sensors is uploaded wirelessly to the cloud server and can be viewed by users from anywhere in the world via an Internet-enabled device. The rugged and water-resistant enclosure ensures that the system can be used in outdoor agriculture fields, while a solar power supply eliminates cabling needs and reduces maintenance of sensor nodes. Tests conducted on the system show that it can successfully capture and display environmental parameter data to users.

Development of a Robotic Arm for Automated Harvesting of Asparagus

We designed and developed an original arm-robot system that harvests asparagus in both outdoor and indoor agricultural fields. Using the system, we carried out harvesting work automatically with input data related to asparagus vegetation in restricted settings. The developed fixed-site (non-wheeled) robot can reach out its arm to a stem of asparagus from a passage between two ridges on cultivated farmland without touching non-target stems or requiring changes to the farm conditions. Additionally, the hand at the tip of the arm stably grasps, cuts, harvests, and throws the stem it into a specific bag made for the gathering of agricultural crops. In mechanical terms, our originally developed robot arm has four degrees of freedom and is driven by motors. It harvests target asparagus stems without coming into contact with other objects in an agricultural setting, and the hand using the linkage mechanism of a pneumatic cylinder driven by air pressure, can hold the stem firmly and cut it. Our repetitive verification experiments showed that the mechanism is sufficiently accurate. The present study confirmed the robot arm system could be used for automatically harvesting asparagus, and the system was endorsed by several farmers. Moreover, we carried out experiments of harvesting asparagus on actual outdoor land and successfully harvested three stems sequentially under the condition that the operator obtained the positional coordinates earlier.

Video Smoke Detection Method Based on Change-Cumulative Image and Fusion Deep Network.

Smoke detection technology based on computer vision is a popular research direction in fire detection. This technology is widely used in outdoor fire detection fields (e.g., forest fire detection). Smoke detection is often based on features such as color, shape, texture, and motion to distinguish between smoke and non-smoke objects. However, the salience and robustness of these features are insufficiently strong, resulting in low smoke detection performance under complex environment. Deep learning technology has improved smoke detection performance to a certain degree, but extracting smoke detail features is difficult when the number of network layers is small. With no effective use of smoke motion characteristics, indicators such as false alarm rate are high in video smoke detection. To enhance the detection performance of smoke objects in videos, this paper proposes a concept of change-cumulative image by converting the YUV color space of multi-frame video images into a change-cumulative image, which can represent the motion and color-change characteristics of smoke. Then, a fusion deep network is designed, which increases the depth of the VGG16 network by arranging two convolutional layers after each of its convolutional layer. The VGG16 and Resnet50 (Deep residual network) network models are also arranged using the fusion deep network to improve feature expression ability while increasing the depth of the whole network. Doing so can help extract additional discriminating characteristics of smoke. Experimental results show that by using the change-cumulative image as the input image of the deep network model, smoke detection performance is superior to the classic RGB input image; the smoke detection performance of the fusion deep network model is better than that of the single VGG16 and Resnet50 network models; the smoke detection accuracy, false positive rate, and false alarm rate of this method are better than those of the current popular methods of video smoke detection.

A deep-level region-based visual representation architecture for detecting strawberry flowers in an outdoor field

An accurate and robust strawberry flower representation and detection scheme is a key step to enable the reliable forecasting of fruit yield for use in precision agricultural applications. A state-of-the-art deep-level object detection framework which processes images through several layers using a region-based convolutional neural network (R-CNN) was developed to visually represent the instances of strawberry flowers in outdoor fields and improve the detection accuracy. A modified version of the visual geometry group 19 (VGG19) architecture, which had 47 layers, was used to represent the multiple scales of strawberry flower image features. The networks were trained entirely on 400 strawberry flower images and tested on another 100 images. Different region-based object detection methods, including the R-CNN, Fast R-CNN and Faster R-CNN, were used to represent the strawberry flower instances. The Faster R-CNN model achieved a better performance than the R-CNN and Fast R-CNN in detecting the instances and had a lower execution time. The detection accuracy of the Faster R-CNN model was 86.1%, which was higher than those of the R-CNN and Fast R-CNN models (63.4% and 76.7%, respectively). The experimental results showed the effectiveness of the deep-level Faster R-CNN framework for representing the strawberry flower instances under various camera view-points, different distances to flowers, overlaps, complex background illumination, blur, etc. The system developed for automatic and accurate strawberry flower detection provides an important and significant solution that enables subsequent applications to estimate the strawberry yield in outdoor fields.

FDTD and Empirical Exploration of Human Body and UWB Radiation Interaction on TOF Ranging

In time-of-flight (TOF)-based human ranging systems, target sensors are often mounted on or close to the human body, which may raise non-line-of-sight (NLOS) cases and lead to significant ranging errors depending on the relative position between the body, transmitter (Tx), and receiver (Rx). In recent years, ultrawideband (UWB) has become a very popular technology for human TOF ranging, but its human body interactions have not been studied yet extensively. In this letter, the UWB and human body interaction is explored by the finite-difference time-domain (FDTD) technique, and the obtained E-field strength variation results are validated by means of commercially available UWB kits. Additionally, an UWB-ranging error model with respect to the human body shadowing effect is proposed and evaluated by extensive measurements, i.e., in indoor environments, line-of-sight (LOS) and NLOS are found to be well modeled by Gaussian and Gamma distributions, respectively, while in outdoor fields, LOS and NLOS are both modeled by Gaussian distributions. The main conclusion of this study is that there is a clear pattern between a gain in the E-field strength and TOF ranging errors. It can be established that in a worst-case scenario, a gain of 4–18 dB is observed, which corresponds to about 30–60 cm of TOF ranging errors.

Stability analysis of PA-6/ethylene elastomer blends for outdoor and nuclear applications

The comparative behaviour under the oxidative degradation occurred during accelerating conditions of ageing (γ-irradiation and artificial weathering) is analysed for three polyamide-6-based formulations destined to special services like outdoor and nuclear fields. Pristine PA-6 and its blends with two ethylene elastomers (ethylene–propylene copolymer and ethylene–acrylic ester terpolymer) grafted with maleic anhydride were tested under accelerated degradation (radiation processing and weathering) by chemiluminescence and swelling. The elastomers are minor components with three loading degrees (5, 10 and 20%). The influence of elastomer fractions on the promotion of oxidation is revealed by the comparison with neat PA-6, which is a most stable of the three involved polymers. The results demonstrate that the minor components are the sources of radicals that are reactive spots. The competition between degradation and partial cross-linking is analysed. The calculated activation energies of oxidation allow the prediction of stability for long-term operation. The mechanistic aspects connected to the availability of blending components to oxidation are discussed for the explanation of ageing propagation under various factors acting during ageing promotion service.