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  <titleInfo>
    <title>Development of IOT-Based Health Monitoring System for Swine</title>
  </titleInfo>
  <name type="personal">
    <namePart>Dumapit, Joanna Mariel T.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
    <role>
      <roleTerm type="text">Author</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Odones, Miguel P.</namePart>
    <role>
      <roleTerm type="text">Author</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Roda, Rosel M.</namePart>
    <role>
      <roleTerm type="text">Author</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Sapungan, Johnelle Irish T.</namePart>
    <role>
      <roleTerm type="text">Author</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">Manila</placeTerm>
    </place>
    <publisher>Technological University of the Philippines</publisher>
    <dateIssued>2025</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>vii, 135 pages: 29cm.</extent>
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  <abstract>Swine farming is a cornerstone of global food security, yet remains highly vulnerable to
rapid disease outbreaks like African Swine Fever (ASF). Traditional health checks rely on
manual observation, which is often slow, labor-intensive, and prone to missing early red
flags such as lethargy or appetite loss. The rationale for this study stems from the immense
economic burden of these diseases; for instance, ASF caused an estimated PHP 50 billion
loss in the Philippines, highlighting the inadequacy of existing diagnostic tools for
smallholder farms. Consequently, the objective of the study was to develop an IoT-based
Swine Monitoring System for early symptom detection to assist resource-limited farmers.
The methodology involved fabricating a waterproof, 3D-printed prototype integrated with
an ESP32 microcontroller and a comprehensive suite of sensors. The system utilized an
AMG8833 IR thermal camera for non-contact body temperature monitoring, an HTU21D
sensor for environmental temperature and humidity, and PIR and ultrasonic sensors to track
animal movement and feeding behavior. Data was transmitted via MQTT protocol to a
dedicated cloud platform called "Babekare," enabling real-time monitoring and immediate
alerts. Experimental results demonstrated high precision, with average percentage errors of
1.50% for thermal readings, 1.60% for motion detection, and 0.28% for food intake
monitoring. While reliability remains sensitive to network stability and sensor calibration,
the system proved effective in identifying early physiological signs of illness. This IoT
solution promotes sustainable livestock practices, reduces economic losses, and improves
overall herd health outcomes.

Keywords: Internet of Things (IoT), Swine Health Monitoring, Thermal Sensor</abstract>
  <note type="statement of responsibility">Joanna Mariel T. Dumapit, Miguel P. Odones, Rosel M. Roda, and Johnelle Irish T. Sapungan..-</note>
  <note>Bachelor's Thesis</note>
  <note>College of Industrial Technology..- Bachelor of Engineering Technology Major in Electronic Communications Technology: Technological University of the Philippines, 2025.</note>
  <note>Includes bibliographic references and index.</note>
  <subject>
    <topic>Electronic Communications Technology</topic>
  </subject>
  <subject>
    <topic>Internet of Things (IoT)</topic>
  </subject>
  <subject>
    <topic>Swine Health Monitoring</topic>
  </subject>
  <classification authority="lcc">BTH TK 5105.59 D86 2025</classification>
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    <recordCreationDate encoding="marc">260616</recordCreationDate>
    <recordChangeDate encoding="iso8601">20260616102409.0</recordChangeDate>
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      <languageTerm authority="iso639-2b" type="code">English</languageTerm>
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