• Journal of Biosystems Engineering
• /
• v.25 no.5
• /
• pp.399-408
• /
• 2000

This study is final focused on developing fruit harvesting robot can distinguish fruit type and status accurately. Multi-joint robot is able to discriminate tree shape and select mature fruit by image processing. The multi-joint robot consists of (a) rotating base, (b)turning first joint-arm, (c)rotating and turning second joint-arm, (d)rotating and turning third joint-arm, (e)rotating and turning last joint and (f)picker hand. The operational ranges of the robot are: horizontal 860~2,220mm, vertical 1,440~2,260mm, 270 degrees’rotation angle, 90 or 270 degrees’turning angle. The robot weighs 330kg. The multi-joint robot was designed in high accuracy and efficiency by getting as close as the movements of human arms and waist.

• Korean Journal of Agricultural Science
• /
• v.46 no.2
• /
• pp.381-393
• /
• 2019

A smart farm is a system that combines information and communication technology (ICT), internet of things (IoT), and agricultural technology that enable a farm to operate with minimal labor and to automatically control of a greenhouse environment. Machine learning based on recently data-driven techniques has emerged with big data technologies and high-performance computing to create opportunities to quantify data intensive processes in agricultural operational environments. This paper presents research on the application of machine learning technology to diagnose the growth status of crops and predicting the harvest time of strawberries in a greenhouse according to image processing techniques. To classify the growth stages of the strawberries, we used object inference and detection with machine learning model based on deep learning neural networks and TensorFlow. The classification accuracy was compared based on the training data volume and training epoch. As a result, it was able to classify with an accuracy of over 90% with 200 training images and 8,000 training steps. The detection and classification of the strawberry maturities could be identified with an accuracy of over 90% at the mature and over mature stages of the strawberries. Concurrently, the experimental results are promising, and they show that this approach can be applied to develop a machine learning model for predicting the strawberry harvesting time and can be used to provide key decision support information to both farmers and policy makers about optimal harvest times and harvest planning.

• Journal of Korea Water Resources Association
• /
• v.53 no.9
• /
• pp.681-690
• /
• 2020

Generally, the design capacity of the rainwater harvesting unit is determined by trial and error method that is repeatedly calculating various analysis scenarios with capacity, reliability, and rainwater utilization ratio, etc. This method not only takes a lot of time to analyze but also involves a lot of calculations, so analysis errors may occur. In order to solve the problem, this study suggested a way to directly determine the minimum capacity to meet arbitrary target reliabilities using the global optimization method. The method was implemented by simulation model with particle swarm optimization (PSO) algorithms using Python language. The pyswarm that is provided as an open-source of python was used as optimization method, that can explore global optimum, and consider constraints. In this study, the developed program was applied to the design data for the rainwater harvesting constructed in Cheongna district 1 in Incheon to verify the efficiency, stability, and accuracy of the analysis. The method of determining the capacity of the rainwater harvesting presented in this study is considered to be of practical value because it can improve the current level of analytical technology.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.05a
• /
• pp.827-830
• /
• 2006

With recent advanced in portable electric devices, wireless sensor, MEMS and bio-Mechanics device, the new typed power supply, not conventional battery but self-powered energy source is needed. Particularly, the system that harvests from their environments are interests for use in self powered devices. For very low powered devices, environmental energy may be enough to use power source. In the generality of cases, these energy harvesting systems are used in the piezoelectric materials as mechanisms to convert mechanical vibration energy into electric energy. Through the piezoelectric materials, the ambient vibration energy could be used to prolong the power supply or in the ideal case provide endless energy f9r the devices. Therefore, the piezoelectric power harvesting cantilever beam is developed. Also, the output voltage and power are predicted in this study. We also discuss the developing system of the piezoelectric energy scavenger. An experimental verification of the model is also performed to ensure its accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.9
• /
• pp.1044-1053
• /
• 2016

In this paper, we consider the secondary users (SUs) who are capable of harvesting energy from ambient radio frequency (RF) signals and are allowed to sequentially sense up to 2 different channels to find out idle channels not occupied by the primary users (PUs). The EH SUs are permitted to transmit data packets only if both idle channels and sufficient energy are available. Compared with traditional SUs, the EH SUs consume energy with data transmission and also harvest energy without additional energy supply. Consequently, the battery state is expected to be fluctuated due to energy consumption and harvesting, and therefore we develop a Markov battery model to provide energy variations at the 2-channel sensing EH SUs. With the proposed battery model, we derive the steady-state probability that the EH SUs completely run out of energy, and the achievable throughput of EH SUs is derived accordingly. To evaluate the proposed Markov battery model, the Monte-Carlo simulation was performed to validate the accuracy of energy outage probability and achievable throughput at the 2-channel sensing EH SUs.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.12 no.2
• /
• pp.108-112
• /
• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.16 no.2
• /
• pp.7-15
• /
• 2017

Recently, an electricity sensor system has been installed and operated to prevent failures and accidents by identifying whether a transformer is normal in advance of failure. This electricity sensor system is able to both measure and monitor the transformer's power and voltage remotely and send information to a manager when unusual operation is discovered. However, a battery is required to operate power detection devices, and battery systems need ongoing management such as regular replacement. In addition, at a maintenance cost, occasional human resources and worker safety problems arise. Accordingly, we apply a linear electromagnetic generator using vibration energy from a transformer for an electric sensor system's drive in this research and we conduct optimal design to maximize the linear electromagnetic generator's power. We consider design variables using the provided design method from Process Integration, Automation, and Optimization (PIAnO), which is common tool from process integration and design optimization (PIDO). In addition, we analyze the experiment point from the design of the experiments using "MAXWELL," which is a common electromagnet analysis program. We then create an approximate model and conduct accuracy verification. Finally, we determine the optimal model that generates the maximum power using the proven approximate kriging model and evolutionary optimization algorithm, which we then confirm via simulation.

• Bulletin of the Korean Chemical Society
• /
• v.35 no.3
• /
• pp.858-864
• /
• 2014

Recently, many researches have shown that even photosynthetic light-harvesting pigment-protein complexes can have quantum coherence in their excitonic energy transfer at cryogenic and physiological temperatures. Because the protein supplies such noisy environment around pigments that conventional wisdom expects very short lived quantum coherence, elucidating the mechanism and searching for an applicability of the coherence have become an interesting topic in both experiment and theory. We have previously studied the quantum coherence of a phycocyanin 645 complex in a marine algae harvesting light system, using Poisson mapping bracket equation (PBME). PBME is one of the applicable methods for solving quantum-classical Liouville equation, for following the dynamics of such pigment-protein complexes. However, it may suffer from many defects mostly from mapping quantum degrees of freedom into classical ones. To make improvements against such defects, benchmarking targets with more accurately described dynamics is highly needed. Here, we fall back to reduced hierarchical equation of motion (HEOM), for such a purpose. Even though HEOM is known to applicable only to simplified system that is coupled to a set of harmonic oscillators, it can provide ultimate accuracy within the regime of quantum-classical description, thus providing perfect benchmark targets for certain systems. We compare the evolution of the density matrix of pigment excited states by HEOM against the PBME results at physiological temperature, and observe more sophisticated changes of density matrix elements from HEOM. In PBME, the population of states with intermediate energies display only monotonically increasing behaviors. Most importantly, PBME suffers a serious issue of wrong population in the long time limit, likely generated by the zero-point energy leaking problem. Future prospects for developments are briefly discussed as a concluding remark.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.6A
• /
• pp.379-387
• /
• 2012

This study investigates free vibration characteristics of new energy harvesting multi-layer block structures with different geometrical shapes using solid and shell finite elements and evaluate their piezoelectric effect on experiments. The two and three-dimensional finite element (FE) delamination models for block structures described in this paper is attractive not only because it shows excellent accuracy in analysis but also it shows the entire vibration mode shape. The FE model using ABAQUS is used for studying free vibrations of multi-layer block structures for various tip mass and PZT. In particular, new results reported in this paper are focused on the significant effects of the global and local vibration modes for various parameters, such as size of block shape, existence of tip mass and hole, and location of tip mass and PZT. In addition, we evaluate the power generation capacity of developed energy block structures through a laboratory-scale experiment.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2000.11b
• /
• pp.287-294
• /
• 2000

Calculation of the flexural rigidity value (EI) is indispensable for prescription of deflection characteristics of crop stalks in harvesting□Conventionally□EI has been determined by either average EI of the whole stalk or average EI of each stems divided into node through the calculation method of cantilever with homogeneous section□However□deflection characteristics of crop stalks caused by mechanical operation such as combine harvester were not exactly presumed by these conventional EI through the experiment by authors. Further, actual EI of a stalk changes in company with a change of moisture contents as time passes during the experiment. Finally, efficient calculation method for determining EI is needed in order to improve these problems. In this study, mechanical model based on actual structure of the crop stalk with variety sectional area was proposed. This mechanical model is calculated by the theory of cantilever with continuous stages. Therefore, improvement of both calculating accuracy on EI and efficiency of measuring system was tried. At first, this calculation method was applied to piano wire of which EI was recognized in advance. As a result, EI calculated from this new method coincided approximately with piano wire's EI. Next, applying to crop stalks as same as piano wire, relationship between loads acting on crop stalks and deflection values calculated by EI using this new calculation method was exactly presumed in comparison with conventional method. Further, measuring time of deflection test was greatly reduced. Finally, new calculation method of EI will be available for estimating mechanical characteristics of so many kinds of crop stalks in harvesting operation. Further, in this study, new deflection test using image-processing apparatus by computer will be introduced.