Arianne P Espinosa
Information and Communication Technology High School
1
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Organizations
3
Awards
2
Papers
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Events
Competitions and programmes taken part in, and in what capacity
FIRA RoboWorld Cup & Summit 2026
Verified by AVISICTHS-Team B · Innovation and Business (U19)
Awards & recognitions
Achievements earned with a team
1st Place
Verified by AVISICTHS-Team B · FIRA RoboWorld Cup & Summit 2026
2nd Place
Verified by AVISICTHS-Team B · FIRA RoboWorld Cup & Summit 2026
1st Place Elevator Pitch
Verified by AVISICTHS-Team B · FIRA RoboWorld Cup & Summit 2026
Conference papers
Research submitted to AVIS conferences
Synchrostream- An Intelligent Sewage Abnormality Detection Apparatus for Smart Cities
The Philippines faces critical challenges in its sewage system, driven by bacterial contamination, chemical contamination, and the accumulation of decaying organic matter. These conditions pose health risks through the emission of harmful gases, such as hydrogen sulfide, methane, ammonia, and carbon dioxide, produced by decaying waste. Moreover, everyday items such as grease, paper towels, and hygiene products are continuously being flushed down drains, clogging the sewer line and further increasing the risk of flooding in these areas. While established solutions focus on wastewater treatment, the researchers propose a different approach—one that focuses on detection to prevent further contamination. SynchroStream is an upgrade to the average sewage system, using four types of sensors to monitor water levels and close grates in the presence of waste, as well as to send data to local authorities via LoRa radio. It utilizes ultrasonic sensors to detect the current water level and debris found in the water. At the same time, a layer of EPDM (ethylene propylene diene monomer) rubber is combined with servo motors to prevent waste from entering the openings. Upon detecting rain using its BMP280 and DHT22, the motors move the rubber to collect rainwater. Additionally, a separate DHT22 sensor and waterflow sensor provide early detection of mosquitoes and notify local government units with updated data about whether there is a need to sanitize and perform maintenance on the area using a machine learning-based predictive maintenance utilizing a Random Forest classification model over the LoRa radio via the ESP32 Development Boards. Then, the data from each sensor is collected by the first ESP32 board and dispatched to the LoRa transmitter. Once it reaches the LoRa receiver, the data is processed by a second ESP32 before being displayed on the dashboard. This project aims to provide an efficient, cost-effective system to mitigate flooding in urban areas and reduce the exposure of the public to toxic gases and diseases associated with them.
Arianne P Espinosa, Celine Kirsten C Mercado, Bernize Lexine M Angeles Verified by AVIS CertificateFIRA World Summit 2026Submitted 5 Jun 2026
Synchrostream- An Intelligent Sewage Abnormality Detection Apparatus for Smart Cities
The Philippines faces critical challenges in its sewage system, driven by bacterial contamination, chemical contamination, and the accumulation of decaying organic matter. These conditions pose health risks through the emission of harmful gases, such as hydrogen sulfide, methane, ammonia, and carbon dioxide, produced by decaying waste. Moreover, everyday items such as grease, paper towels, and hygiene products are continuously being flushed down drains, clogging the sewer line and further increasing the risk of flooding in these areas. While established solutions focus on wastewater treatment, the researchers propose a different approach—one that focuses on detection to prevent further contamination. SynchroStream is an upgrade to the average sewage system, using four types of sensors to monitor water levels and close grates in the presence of waste, as well as to send data to local authorities via LoRa radio. It utilizes ultrasonic sensors to detect the current water level and debris found in the water. At the same time, a layer of EPDM (ethylene propylene diene monomer) rubber is combined with servo motors to prevent waste from entering the openings. Upon detecting rain using its BMP280 and DHT22, the motors move the rubber to collect rainwater. Additionally, a separate DHT22 sensor and waterflow sensor provide early detection of mosquitoes and notify local government units with updated data about whether there is a need to sanitize and perform maintenance on the area using a machine learning-based predictive maintenance utilizing a Random Forest classification model over the LoRa radio via the ESP32 Development Boards. Then, the data from each sensor is collected by the first ESP32 board and dispatched to the LoRa transmitter. Once it reaches the LoRa receiver, the data is processed by a second ESP32 before being displayed on the dashboard. This project aims to provide an efficient, cost-effective system to mitigate flooding in urban areas and reduce the exposure of the public to toxic gases and diseases associated with them.
Arianne P Espinosa, Celine Kirsten C Mercado, Bernize Lexine M Angeles Verified by AVIS CertificateFIRA World Summit 2026Submitted 5 Jun 2026
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