Dan Jeric Arcega Rustia

Dan Jeric Arcega Rustia
Wageningen University & Research | WUR · Wageningen UR Greenhouse Horticulture

PhD in Biomechatronics Engineering

About

31
Publications
12,898
Reads
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207
Citations
Additional affiliations
March 2021 - October 2021
National Taiwan University
Position
  • PostDoc Position
March 2021 - March 2022
De La Salle University
Position
  • Associate Professor
Education
September 2016 - March 2021
National Taiwan University
Field of study
  • PhD in Biomechatronics Engineering
September 2014 - January 2016
Chung Yuan Christian University
Field of study
  • MSc in Electronics Engineering
June 2010 - March 2014
University of Santo Tomas
Field of study
  • BS in Applied Physics Major in Instrumentation

Publications

Publications (31)
Article
This work presents an automated insect pest counting and environmental condition monitoring system using integrated camera modules and an embedded system as the sensor node in a wireless sensor network. The sensor node can be used to simultaneously acquire images of sticky paper traps and measure temperature, humidity,and light intensity levels in...
Article
Inspection of insect sticky paper traps is an essential task for an effective integrated pest management (IPM) programme. However, identification and counting of the insect pests stuck on the traps is a very cumbersome task. Therefore, an efficient approach is needed to alleviate the problem and to provide timely information on insect pests. In thi...
Article
The unavailability and variability of training samples are the two essential concerns in the training of deep neural network models for image classification. For automated image monitoring systems, these problems are difficult when training a model through supervised learning methods because of the time and effort required. This paper proposes an a...
Article
Background: Main bottleneck in facilitating integrated pest management (IPM) is the unavailability of reliable and immediate crop damage data. Without sufficient insect pest and plant disease information, farm managers are unable to make proper decisions to prevent crop damage. This work aims to present how an integrated system was able to drive f...
Conference Paper
Full-text available
One of the issues in training a deep learning-based object detector is the imbalance in the number of objects found in an image. This makes an object detector inadequately trained on different backgrounds and varying numbers of objects. To propose a solution to this problem, this work presents a method for generating synthetic cocoa pod borer (CPB)...
Conference Paper
Full-text available
Indoor crop production requires multiple trials to determine which conditions and parameters help in optimizing plant growth. A solution for this problem is to promptly detect nutrient deficiency. This paper proposes an artificial intelligence of things (AIoT)-based system that aims to monitor plant growth and detect stunted plant growth caused by...
Conference Paper
Full-text available
The cocoa pod borer (CPB) (Conopomorpha cramerella) is a very small insect pest native to Asia and Oceania. CPBs cause extensive damage by boring holes into cocoa pod husks and cause premature ripening. Due to its resemblance to other insect pest species, most farm managers fail to recognize it; this makes farm managers unable to avert crop damage....
Article
Heat stress is one of the major challenges in livestock production and management. Due to heat stress, dairy cows experience health and fertility problems as well as lower milk production, resulting in great economic losses to dairy farmers. One of the approaches to assessing heat stress in dairy cows is by monitoring their respiration rate (RR). M...
Article
Pollen foraging efficiency provides vital information for the behavioral research on honey bees. The pollen production of beehives can be measured by manually weighing the pollen collected from pollen traps. For long-term pollen foraging monitoring, this approach is both inefficient and laborious. This study presents an efficient method for automat...
Article
Full-text available
The population loss rate of a honey bee colony is a critical index to verify its health condition. Forecasting models for the population loss rate of a honey bee colony can be an essential tool in honey bee health management and pave away to early warning methods in the understanding of potential abnormalities affecting a honey bee colony. This wor...
Conference Paper
Full-text available
The inability to classify insects up to the species level is the current limitation of recently developed automated insect recognition algorithms. Yet, there are situations in integrated pest management (IPM) that call for more precise classification of insects. This research proposes an effective method for automated identification of low-resoluti...
Conference Paper
Full-text available
With the advances of computer vision over the recent years, its applications have extended from handling static images to tackling the challenging domain of video analysis, with human activity recognition being among the core research topics. However, recognizing and recording the activity of agricultural workers through surveillance videos is stil...
Conference Paper
Full-text available
Tomato (Solanum lycopersicum L.) is a high-value crop all over the world. This means that systematic and intensive management of tomato crops is necessary. To assist in achieving this goal, this paper presents an early warning system for tomato bacterial spot disease (TBSD) (Xanthomonas perforans) and tomato black leaf mold disease (TBLM) (Pseudoce...
Conference Paper
Full-text available
瞭解害蟲種類與其密度可以幫助農民進行農藥施用與農場管理之決策。然而,在沒有 使用自動化工具的情形下,定期檢查黏蟲紙上的害蟲作業會是一份非常繁瑣的工作。本研究 開發了 I2PM camera,一個用於針對黏蟲紙影像之害蟲偵測與計數的手機或行動裝置應用程 式。該應用程式允許使用者拍攝並上傳黏蟲紙影像至伺服器,影像使用級聯式深度學習辨識 模型進行處理。程式會顯示處理後的影像、害蟲數量與密度,若是積累的資料足夠,也會顯 示歷史數據圖。為了使程式能夠廣泛適用於各種拍攝環境,軟體亦開發一套拍攝與預處理的 標準流程。黏蟲紙影像是由多個溫室所蒐集,並用於訓練深度學習模型。目前該程式可識別 四種害蟲:蒼蠅 (雙翅目:Drosophilia)、蚊蚋 (雙翅目:Sciaridae)、薊馬 (纓翅目:Thripid...
Article
Full-text available
To counteract heat stress in dairy cows, a more reliable and efficient method for monitoring the activity of dairy cows and ambient environmental conditions should be developed. This research presents a cost-effective embedded imaging system that is capable of monitoring the drinking behaviour of dairy cows, while ambient temperature and humidity a...
Article
The application of deep neural networks in computer vision has remarkably improved the reliability of automated insect pest identification algorithms. However, to build a robust deep neural network classifier model, sufficient number of image data is necessary. In preparing image data, collection and annotation of large datasets can be labor-intens...
Article
Greenhouse whitefly (Trialeurodes vaporariorum) is a major insect pest of greenhouse crops. To prevent the damage caused by whiteflies, farmers control the population of whiteflies by spraying pesticides in a regular basis. However, pesticides are costly and may affect the environment and health of farmers. To provide a more efficient way for apply...
Conference Paper
Trialeurodes vaporariorum, commonly known as greenhouse whitefly, is one of the most critical insect pests in greenhouses, causing crop damages every year. Greenhouse whitefly is also a common vector for transmitting numerous plant diseases. Due to this, controlling and predicting the population of whiteflies is one of the most essential issue in g...
Patent
Full-text available
A pest surveillance system comprising at least one pest monitoring apparatus and a main server is provided. The pest monitoring apparatus comprises an image capturing device, an environmental status sensing device, a controller and a network transmitter. The at least one pest monitoring apparatus is disposed in at least one space. The image capturi...
Article
Full-text available
One of the most harmful greenhouse insect pests is the Trialeurodes vaporariorum or most commonly known as the greenhouse whitefly. The easiest way to monitor the population of greenhouse whiteflies is by the use of yellow sticky paper traps. The insect count information from the traps can be used for analyzing insect behavior by constructing biolo...
Conference Paper
Full-text available
Insect pest identification is very important for greenhouse management. Having the knowledge of what insects exist in their greenhouse, farmers will be able to determine which pesticide will be more effective to prevent insect pest outbreaks and protect their crops. The most common technique to monitor insect pests is the use of strips of yellow st...
Conference Paper
Full-text available
A technique for real-time insect pest counting using object classifiers through support vector machine (SVM) is presented on this paper. The objects are detected through RGB-LUV color segmentation and blob detection. The objects are classified into insect and non-insects in which the non-insects are sub-classified into glares or droplets. This appr...
Article
Full-text available
This study focuses on designing an Internet of Things (IoT) based remote greenhouse pest monitoring system using wireless imaging and sensor nodes (WiSN). The system designed can continuously monitor the number of pest insects detected on yellow sticky papers distributed in multiple locations and can measure the environmental parameters simultaneou...
Article
We present an electronic tongue system composed of an analog front-end (AFE) with embedded calibration and temperature compensation for interfacing with an array of Ion-Sensitive FETs (ISFETs) or Enzyme – Extended Gate FETs (EEGFET). The AFE consists of a floating bridge type constant voltage constant current (CVCC) structure, and transmission gate...
Article
In this paper, the design of an on-board and system on-chip Bio-Impedance Spectroscopy (BIS) mixed-signal system is presented. It consists of a Direct Digital Synthesis Sine-Wave Generator (DDS-SWG), an Analog Front-End (AFE), an Analog-Digital Converter (ADC), and a Digital Back-End implemented on a Field Programmable Gate Array (FPGA). The FPGA d...
Conference Paper
This work presents a system for point-of-care testing of urine quality through conductivity and pH. The conductometric system consists of a DDS sine-wave generator, current source and instrumentation amplifiers. The potentiometric readout consists of a floating bridge-type CVCC circuit with transmission gates for interfacing with FET-based sensor a...
Conference Paper
Full-text available
The system presented in this paper is a multi-functional monitoring and control system that aims to provide data collection and interpretation with feedback control for faster plant production and higher crop yield. It can be accessed through local Wi-Fi connection or remote internet access through any portable device. The crop used for the testing...
Conference Paper
Full-text available
An IoT(Internet-of-Things)-based monitoring system with environmental condition monitoring using wireless sensor networks as support for an in and out honeybee activity tracking system using real-time image processing is presented in this paper. The system provides real-time updates, data management, statistical analysis, and alerts through a websi...
Conference Paper
Full-text available
The web controllable greenhouse control system is an Internet-of-Things (IOT) system composed of an ESP8266 module for WiFi communication, server-handling, and database client, an ATMEGA328 MCU for relay and sensor controls, and a Raspberry Pi for webcam control and as the database server. A smart greenhouse control system was designed with both ma...

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Projects

Projects (2)
Project
To monitor the in-out behavior of honey bees through an imaging system using deep learning and image processing. This also includes applying deep learning techniques for forecasting and detecting honey bee colony collapse.
Project
Monitoring of insect pests using wireless imaging sensors for integrated pest management