• Title/Summary/Keyword: Sensor & Cloud Technology

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Development and Application of Arduino Based Multi-sensors System for Agricultural Environmental Information Collection - A Case of Hog Farm in Yeoju, Gyeonggi - (농업환경정보 수집을 위한 아두이노 기반 멀티 센서 시스템 개발 및 적용 - 경기 여주시 소재 양돈농가를 사례로 -)

  • Han, Jung-Heon;Park, Jong-Jun
    • Journal of Korean Society of Rural Planning
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    • v.25 no.2
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    • pp.15-21
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    • 2019
  • The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

In-orbit Stray Light Analysis for Step and Stare observation at Geostationary Orbit

  • Oh, Eunsong;Hong, Jinsuk;Ahn, Ki-Beom;Cho, Seongick;Ryu, Joo-Hyung;Kim, Sug-Whan
    • The Bulletin of The Korean Astronomical Society
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    • v.37 no.2
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    • pp.218.2-218.2
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    • 2012
  • In the remote sensing researches, the reflected bright source such as snow, cloud have effects on the image quality of wanted signal. Even though those signal from bright source are adjusted in corresponding pixel level with atmospheric correction algorithm or radiometric correction, those can be problem to the nearby signal as one of the stray light source. Especially, in the step and stare observational method which makes one mosaic image with several snap shots, one of target area can affect next to the other snap shot each other. Presented in this paper focused on the stray light analysis from unwanted reflected bright source for geostationary ocean color sensor. The stray light effect for total 16 slot images each other were performed according to 8 band filters. For the realistic simulation, we constructed system modeling with integrated ray tracing technique which realizes the same space time in the remote sensing observation among the Sun, the Earth, and the satellite. Computed stray light effect in the results of paper demonstrates the distinguishable radiance value at the specific time and space.

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Unsupervised Monocular Depth Estimation Using Self-Attention for Autonomous Driving (자율주행을 위한 Self-Attention 기반 비지도 단안 카메라 영상 깊이 추정)

  • Seung-Jun Hwang;Sung-Jun Park;Joong-Hwan Baek
    • Journal of Advanced Navigation Technology
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    • v.27 no.2
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    • pp.182-189
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    • 2023
  • Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.

The Singular Economy: End of the Digital/Physical Divide

  • Meceda, Ann M.;Vonortas, Nicholas S.
    • STI Policy Review
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    • v.9 no.1
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    • pp.133-157
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    • 2018
  • The divide between the "digital" economy and the traditional "physical" economy is outdated. In fact, we are in a transition to a singular economy. This paper classifies economic objects (including actors) as either physical or virtual and argues that due to emerging technologies, these objects are interacting with each other in both physical and increasingly digital spheres in tandem. This paper recognizes the elemental difference between atoms and bytes but argues that physical and digital economic activities are becoming inseparably intertwined. Furthermore, arbitrarily dividing the economy into two categories - one "physical" and the other "digital" - distorts the overall view of the actual execution of economic activity. A wide range of innovations emerging concurrently is fueling the transition to a singular economy. Often referred to as the elements of the Fourth Industrial Revolution (4IR), four emerging technological areas are reviewed here: distributed ledger technology, artificial intelligence/machine learning/data sciences, biometrics and remote sensor technologies, and access infrastructure (universal internet access/electricity/cloud computing). The financial services sector is presented as a case study for the potential impact of these 4IR technologies and the blurring physical/digital line. To reach the potential of these innovations and a truly singular economy, it requires the concurrent development of social, organizational, and regulatory innovations, though they lag in terms of technological progress thus far.

Collision Avoidance Sensor System for Mobile Crane (전지형 크레인의 인양물 충돌방지를 위한 환경탐지 센서 시스템 개발)

  • Kim, Ji-Chul;Kim, Young Jea;Kim, Mingeuk;Lee, Hanmin
    • Journal of Drive and Control
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    • v.19 no.4
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    • pp.62-69
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    • 2022
  • Construction machinery is exposed to accidents such as collisions, narrowness, and overturns during operation. In particular, mobile crane is operated only with the driver's vision and limited information of the assistant worker. Thus, there is a high risk of an accident. Recently, some collision avoidance device using sensors such as cameras and LiDAR have been applied. However, they are still insufficient to prevent collisions in the omnidirectional 3D space. In this study, a rotating LiDAR device was developed and applied to a 250-ton crane to obtain a full-space point cloud. An algorithm that could provide distance information and safety status to the driver was developed. Also, deep-learning segmentation algorithm was used to classify human-worker. The developed device could recognize obstacles within 100m of a 360-degree range. In the experiment, a safety distance was calculated with an error of 10.3cm at 30m to give the operator an accurate distance and collision alarm.

AR-based 3D Digital Map Visualization Support Technology for Field Application of Smart Construction Technology

  • Song, Jinwoo;Hong, Jungtaek;Kwon, Soonwook
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1255-1255
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    • 2022
  • Recently, research on digital twins to generate digital information and manage construction in real-time using advanced technology is being conducted actively. However, in the construction industry, it is difficult to optimize and apply digital technology in real-time due to the nature of the construction industry in which information is constantly fluctuating. In addition, inaccurate information on the topography of construction projects is a major challenge for earthmoving processes. In order to ultimately improve the cost-effectiveness of construction projects, both construction quality and productivity should be addressed through efficient construction information management in large-scale earthworks projects. Therefore, in this study, a 3D digital map-based AR site management work support system for higher efficiency and accuracy of site management was proposed by using unmanned aerial vehicles (UAV) in wide earthworks construction sites to generate point cloud data, building a 3D digital map through acquisition and analysis of on-site sensor-based information, and performing the visualization with AR at the site By utilizing the 3D digital map-based AR site management work support system proposed in this study, information is able to be provided quickly to field managers to enable an intuitive understanding of field conditions and immediate work processing, thereby reducing field management sluggishness and limitations of traditional information exchange systems. It is expected to contribute to the improvement of productivity by overcoming factors that decrease productivity in the construction industry and the improvement of work efficiency at construction sites.

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4 to 18 GHz Rader Backscatter Model of Frist-Year Sea Ice

  • Kim, Young-Soo
    • Korean Journal of Remote Sensing
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    • v.3 no.2
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    • pp.89-102
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    • 1987
  • Microwave remote sensing plays a major role in areas where cloud cover and darkness prevail. In this and the next paper, models are described for the radar backscatter from two major types of sea ice in an attempt to specify optimum sensor parameters and to allow the most reliable image interpretation possible. Here, the physical-optics model using an exponential correlation function is shown to be able to presict the signatures of first-year ice under cold conditions. The effect of volume scattering by small inclusions in the first-year ics is shown to be negligible using a semi-empirical volume scattering model.

Adaptive Reconstruction Of AVHRR NVI Sequential Imagery off Korean Peninsula

  • Lee, Sang-Hoon;Kim, Kyung-Sook
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.63-82
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    • 1994
  • Multitemporal analysis with remotely sensed data is complicated by numerous intervening factors, including atmospheric attenuation and occurrence of clouds that obscure the relationship between ground and satellite observed spectral measurements. A reconstruction system was developed to increase the discrimination capability for imagery that has been modified by residual dffects resulting from imperfect sensing of the target and by atmospheric attenuation of the signal. Utilizing temporal information based on an adaptive timporal filter, it recovers missing measurements resulting from cloud cover and sensor noise and enhances the imagery. The temporal filter effectively tracks a systematic trend in remote sensing data by using a polynomial model. The reconstruction system were applied to the AVHRR data collected over Korean Peninsula. The results show that missing measurements are typically recovered successfully and the temporal trend in vegetation change is exposed clearly in the reconstructed series.

Extraction of 3D Objects Around Roads Using MMS LiDAR Data (MMS LiDAR 자료를 이용한 도로 주변 3차원 객체 추출)

  • CHOUNG, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.1
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    • pp.152-161
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    • 2017
  • Making precise 3D maps using Mobile Mapping System (MMS) sensors are essential for the development of self-driving cars. This paper conducts research on the extraction of 3D objects around the roads using the point cloud acquired by the MMS Light Detection and Ranging (LiDAR) sensor through the following steps. First, the digital surface model (DSM) is generated using MMS LiDAR data, and then the slope map is generated from the DSM. Next, the 3D objects around the roads are identified using the slope information. Finally, 97% of the 3D objects around the roads are extracted using the morphological filtering technique. This research contributes a plan for the application of automated driving technology by extracting the 3D objects around the roads using spatial information data acquired by the MMS sensor.

Transparent Manipulators Accomplished with RGB-D Sensor, AR Marker, and Color Correction Algorithm (RGB-D 센서, AR 마커, 색수정 알고리즘을 활용한 매니퓰레이터 투명화)

  • Kim, Dong Yeop;Kim, Young Jee;Son, Hyunsik;Hwang, Jung-Hoon
    • The Journal of Korea Robotics Society
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    • v.15 no.3
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    • pp.293-300
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    • 2020
  • The purpose of our sensor system is to transparentize the large hydraulic manipulators of a six-ton dual arm excavator from the operator camera view. Almost 40% of the camera view is blocked by the manipulators. In other words, the operator loses 40% of visual information which might be useful for many manipulator control scenarios such as clearing debris on a disaster site. The proposed method is based on a 3D reconstruction technology. By overlaying the camera image from front top of the cabin with the point cloud data from RGB-D (red, green, blue and depth) cameras placed at the outer side of each manipulator, the manipulator-free camera image can be obtained. Two additional algorithms are proposed to further enhance the productivity of dual arm excavators. First, a color correction algorithm is proposed to cope with the different color distribution of the RGB and RGB-D sensors used on the system. Also, the edge overlay algorithm is proposed. Although the manipulators often limit the operator's view, the visual feedback of the manipulator's configurations or states may be useful to the operator. Thus, the overlay algorithm is proposed to show the edge of the manipulators on the camera image. The experimental results show that the proposed transparentization algorithm helps the operator get information about the environment and objects around the excavator.