• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.408-417
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• 2016

Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% ($R^2=0.99$). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3544-3564
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• 2022

With the development of the NB-IoT (Narrow band Internet of Things) and smart cities, coupled with the emergence of smart smoke sensors, new requirements and issues have been introduced to study on the deployment of sensors in large spaces. Previous research mainly focuses on the optimization of wireless sensors in some monitoring environments, including three-dimensional terrain or underwater space. There are relatively few studies on the optimization deployment problem of smart smoke sensors, and leaving large spaces with obstacles such as libraries out of consideration. This paper mainly studies the deployment issue of smart smoke sensors in large spaces by considering the fire probability of fire areas and the obstacles in a monitoring area. To cope with the problems of coverage blind areas and coverage redundancy when sensors are deployed randomly in large spaces, we proposed an optimized deployment strategy of smart smoke sensors based on the PSO (Particle Swarm Optimization) algorithm. The deployment problem is transformed into a multi-objective optimization problem with many constraints of fire probability and barriers, while minimizing the deployment cost and maximizing the coverage accuracy. In this regard, we describe the structure model in large space and a coverage model firstly, then a mathematical model containing two objective functions is established. Finally, a deployment strategy based on PSO algorithm is designed, and the performance of the deployment strategy is verified by a number of simulation experiments. The obtained experimental and numerical results demonstrates that our proposed strategy can obtain better performance than uniform deployment strategies in terms of all the objectives concerned, further demonstrates the effectiveness of our strategy. Additionally, the strategy we proposed also provides theoretical guidance and a practical basis for fire emergency management and other departments to better deploy smart smoke sensors in a large space.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.172-172
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• 2023

The use of low-cost IoT sensors for flow measurement in open channels has gained significant attention due to their potential to provide continuous and real-time data at a low cost. However, the accuracy and reliability of these sensors in real-world scenarios are not well understood. This study aims to compare the performance of low-cost IoT sensors in the laboratory and real-world conditions to evaluate their accuracy and reliability. Firstly, a low-cost IoT sensor was integrated with an IoT platform to acquire real-time flow rate data. The IoT sensors were calibrated in the laboratory environment to optimize their accuracy, including different types of low-cost IoT sensors (HC-SR04 ultrasonic sensor & YF-S201 sensor) using an open channel prototype. After calibration, the IoT sensors were then applied to a real-world case study in the Dorim-cheon stream, where they were compared to traditional flow measurement methods to evaluate their accuracy.The results showed that the low-cost IoT sensors provided accurate and reliable flow rate data under laboratory conditions, with an error range of less than 5%. However, when applied to the real-world case study, the accuracy of the IoT sensors decreased, which could be attributed to several factors such as the effects of water turbulence, sensor drift, and environmental factors. Overall, this study highlights the potential of low-cost IoT sensors for flow measurement in open channels and provides insights into their limitations and challenges in real-world scenarios.

• Journal of the Korean Electrochemical Society
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• v.27 no.1
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• pp.1-7
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• 2024

With the increasing demand for wearable sensors that are capable of point-of-care testing, paper-based sensors have been extensively studied. Paper is not only extremely cost-effective but also lightweight and flexible, and it is easy to apply conductive materials such as carbon and hydrophobic substances like wax to its surface. Moreover, the capillary action caused by cellulose fibers in paper allows the flow of liquid without help from external forces, making paper a particularly promising platform for wearable electrochemical sensors. Accordingly, paper-based sensors for detecting various analytes through electrochemical methods have been actively developed. Recently, paper-based electrochemical sensors that utilize electrochemiluminescence (ECL) or electrochromic materials for the optical read-out have been reported. This review introduces the basic fabrication methods and various application strategies of paper-based electrochemical sensors.

• Electronics and Telecommunications Trends
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• v.33 no.1
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• pp.123-130
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• 2018

Tactile sensors, which are commonly referred to as pressure and strain sensors, have been extensively investigated to meet the demands for attachable and wearable electronics for monitoring the health status or activity of human users. For this purpose, the introduction of two-dimensional (2D) materials such as graphene and transition metal dichalcogenides (TMDs) with high mechanical strength at the atomic scale is very suitable for tactile sensors applicable for use in human-friendly devices. In this paper, we examine a descriptive summary of a tactile sensor and review state-of- the-art research trends of 2D material-based tactile sensors in terms of the material and architecture. Finally, we propose a roadmap for future studies into advanced tactile sensors based on our ongoing research.

• International journal of advanced smart convergence
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• v.3 no.2
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• pp.14-17
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• 2014

Precision agriculture relies on information technology, whose precondition is providing real-time and accurate information. It depends on various kinds of advanced sensors, such as environmental temperature and humidity, wind speed, light intensity, and other types of sensors. Currently, it is a hot topic how to collect accurate information, the main raw data for agricultural experts, monitored by these sensors timely. Most existing work in WSNs addresses their fundamental challenges, including power supply, limited memory, processing power and communication bandwidth and focuses entirely on their operating system and networking protocol design and implementation. However, it is not easy to find the self-localization capability of wireless sensor networks. Because of constraints on the cost and size of sensors, energy consumption, implementation environment and the deployment of sensors, most sensors do not know their locations. This paper provides maximum likelihood estimators for sensor location estimation when observations are time-of arrival (TOA) range measurement.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1012-1014
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• 2003

Since it's establishment Malaysian Center for Remote Sensing (MACRES) has focused on the measurements from airborne and space borne remote sensors. In the year 1999 MACRES in collaboration with Multimedia University Malaysia (MMU) began developing it's own remote sensing sensors to meet Malaysian Remote Sensing needs. MACRES adopted a very systematic approached to the development of these microwave sensors. Starting from non-imaging ground base microwave remote sensing sensors MACRES is now well into developing it's first Airborne Synthetic Aperture Radar. With the capability of developing it's own sensors MACRES will profit more on the microwave remote sensing application research. This paper will demonstrate MACRES capability in developing Microwave Remote Sensing Sensors to meet Malaysian remote sensing society needs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1692-1698
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• 2010

In this paper we use wireless sensor network and ultrasonic sensors to estimate local position of mobile robots, and to navigate it. Ultra sonic sensor is simple and accurate so it is good to use in local estimation and navigation of mobile robots. But to obtain accurate distance of two sensors they need to face each others as possible as they can. To solve this problem we rotate ultra sonic sensor which is attached to robot in 360 degrees and obtain accurate distance. We can estimate precise position of mobile robot by triangulation using obtained distance information. A mobile robot navigates using embedded encoder and compensates its coordinates by ultrasonic sensors. Results of Experiments show proposed method obtains accurate distance between sensors and coordinates of position of robot. And mobile robots can navigate designated path well.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.938-942
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• 2007

The proposed algorithm tries to localize damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides an effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• Transactions of the Korean Society of Automotive Engineers
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• v.25 no.3
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• pp.309-316
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• 2017

In shuttle vans designed to transport children, the recognition of a child's approach and departure is very important. Ultrasonic sensors are generally used for a short distance around a vehicle. Although ultrasonic sensors are cheaper than other ADAS sensors, the number of sensors installed in a van should be optimized. In order to recognize the presence of a child around a shuttle van, this paper proposes the placement of ultrasonic sensors in the van. Considering the turning radius of the van and the distance from each sensor to a child, collision risk is classified as 'safe', 'warning', and 'danger'. The sensor placement and the recognition algorithm are verified in a virtual driving environment.