• Title/Summary/Keyword: Thermal Infra-Red Sensors

Search Result 5, Processing Time 0.018 seconds

A Study on the Best Applicationsof Infra-Red(IR) Sensors Mounted on the Unmanned Aerial Vehicles(UAV) in Agricultural Crops Field (무인기 탑재 열화상(IR) 센서의 농작물 대상 최적 활용 방안 연구)

  • Ho-Woong Shon;Tae-Hoon Kim;Hee-Woo Lee
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.26 no.6_2
    • /
    • pp.1073-1082
    • /
    • 2023
  • Thermal sensors, also called thermal infrared wavelength sensors, measure temperature based on the intensity of infrared signals that reach the sensor. The infrared signals recognized by the sensor include infrared wavelength(0.7~3.0㎛) and radiant infrared wavelength(3.0~100㎛). Infrared(IR) wavelengths are divided into five bands: near infrared(NIR), shortwave infrared(SWIR), midwave infrared(MWIR), longwave infrared(LWIR), and far infrared(FIR). Most thermal sensors use the LWIR to capture images. Thermal sensors measure the temperature of the target in a non-contact manner, and the data can be affected by the sensor's viewing angle between the target and the sensor, the amount of atmospheric water vapor (humidity), air temperature, and ground conditions. In this study, the characteristics of three thermal imaging sensor models that are widely used for observation using unmanned aerial vehicles were evaluated, and the optimal application field was determined.

CNN-based People Recognition for Vision Occupancy Sensors (비전 점유센서를 위한 합성곱 신경망 기반 사람 인식)

  • Lee, Seung Soo;Choi, Changyeol;Kim, Manbae
    • Journal of Broadcast Engineering
    • /
    • v.23 no.2
    • /
    • pp.274-282
    • /
    • 2018
  • Most occupancy sensors installed in buildings, households and so forth are pyroelectric infra-red (PIR) sensors. One of disadvantages is that PIR sensor can not detect the stationary person due to its functionality of detecting the variation of thermal temperature. In order to overcome this problem, the utilization of camera vision sensors has gained interests, where object tracking is used for detecting the stationary persons. However, the object tracking has an inherent problem such as tracking drift. Therefore, the recognition of humans in static trackers is an important task. In this paper, we propose a CNN-based human recognition to determine whether a static tracker contains humans. Experimental results validated that human and non-humans are classified with accuracy of about 88% and that the proposed method can be incorporated into practical vision occupancy sensors.

Heat Source Identification Technique of Aircraft and Flare using 2-color Detectable Infrared Sensors (복수 대역 감지 적외선 센서를 이용한 항공기와 플레어의 열원 식별 기술)

  • Lee, Dong-Si;Lee, Kee-Keun
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.64 no.7
    • /
    • pp.1031-1039
    • /
    • 2015
  • Present guided missiles are equipped with infrared seeker to find the infrared sources radiating from target plane and then chase, which results in an improvement of the hitting success rate when in striking target objects. To interrupt the chases from the guided missile, the target plane spreads the flare, avoiding the missile attracts. Our research is to develop a 2-color infrared identification technique to discern the flare and real thermal source from target plane. Considering flare radiation properties and EM atmosphere transmission rates, two channels were selected, in which main channel (MC) was in a range of 3.7 μm∼4.8 μm and auxiliary channel (AC) in 1.7 μm∼2.3 μm. A 2500K heat source was used for an artificial flare source, while a 570K heat source was utilized for airplane infrared source in experimental testing. Two infrared sensors detectable only at each chanel were employed in order to measure the voltage ratio from two channels, identifying the flare and real target plane via comparison the voltage ratio. Several experimental conditions were imported in order to prove that our proposed 2-color infrared identification technique is very efficient way to discern heat sources from aircraft and flare, demonstrating that our proposed technique is very promising means for our force’s InfraRed Counter Counter Measure (IRCCM) in order to countermeasure opposite force’s InfraRed Counter Measures (IRCM).

Measurements of Temperature Distribution on Human Body Surface using Multi-Channel Skin Temperature Sensors (다채널 피부온 센서를 이용한 인체표면 온도분포의 측정)

  • 한화택;김민규;박명규;이성수
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
    • /
    • 2002.05a
    • /
    • pp.205-209
    • /
    • 2002
  • 인체의 피부온도는 쾌적성과 감성에 크게 영향을 미치며 의류의 개발이나 건축환경의 설계 등에 활용되고 있다. 단순히 몇몇 측정점에서의 피부온도 데이터가 아니라 인체표면에 걸친 온도분포를 파악함으로써 다양한 정보를 이용하여 보다 광범위한 응용분야에 활용될 수 있을 것이다. 현재 인체표면의 온도분포를 측정하기 위하여 대부분 적외선 열화상 카메라를 활용하고 있다 그러나 열화상 카메라는 서미스터 등을 이용한 피부온 센서에 비하여 온도분해능이 떨어지며 특히 의복내의 피부온을 측정하는 것이 불가능하고 노출된 인체표면에 대해서만 측정이 가능하다. 따라서 본 연구에서는 피부온 센서를 이용한 인체표면 온도분포 측정시스템을 개발하기 위하여 각 센서의 위치와 간격, 그리고 인체 곡면을 따라서 보간법에 따라 온도분포 결과에 미치는 영향을 파악하고 적외선 화상 결과와 비교하고자 한다.

  • PDF

Assessment of the Relationship between Air Temperature and TOA Brightness Temperature in Different Seasons Using Landsat-8 TIRS (Landsat-8 위성의 열적외 센서를 활용한 대기온도와 밝기온도의 계절별 상관관계 분석)

  • CHOUNG, Yun-Jae;CHUNG, Youn-In;CHOI, Soo-Young
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.21 no.2
    • /
    • pp.68-79
    • /
    • 2018
  • In general, Top Of Atmosphere(TOA) brightness temperature is closely related to air temperature. Brightness temperature can be derived from the Thermal Infra-Red Sensors (TIRS) of the earth observation satellites such as the Landsat series. The TIRS instrument of the Landsat-8 satellite collects the two spectral bands (Bands 10 and 11) that measure brightness temperature. In this research, the relationship between the air temperature data measured by the weather stations in Seoul, South Korea and the brightness temperature data separately derived from Bands 10 and 11 of the Landsat-8 satellite were assessed in the different seasons through the correlation analysis. The statistical results led to the following conclusions. First, brightness temperature is closely related to air temperature in order of Spring, Autumn, Winter and Summer. Second, when air temperature increases, brightness temperature also increases in Spring, Autumn and Winter but decreases in Summer. Third, Band 10 has a closer relationship to air temperature than Band 11.