Embedded Wireless Stingless Beehive Monitoring And Data Management System Noor Hafizah Khairul Anuar School of Electrical Engineering, Universiti Teknologi Malaysia Skudai, Malaysia Faculty of Electrical Engineering, Universiti Teknologi MARA Pasir Gudang, Malaysia noorhafizah2575@uitm.edu.my Sallehuddin Ibrahim Control and Mechatronics Engineering School of Electrical Engineering, Universiti Teknologi Malaysia Skudai, Malaysia sallehuddin@utm.my Mohd Amri Md Yunus Frontier Materials Research Alliance , Control and Mechatronics Engineering Division School of Electrical Engineering, Universiti Teknologi Malaysia Skudai, Malaysia amri@fke.utm.my Shafishuhaza Sahlan Control and Mechatronics Engineering School of Electrical Engineering, Universiti Teknologi Malaysia Skudai, Malaysia shafis@utm.my Muhammad Ariff Baharudin Control and Mechatronics Engineering School of Electrical Engineering, Universiti Teknologi Malaysia Skudai, Malaysia ariff@utm.my Abstract—In this paper, an embedded wireless stingless bee monitoring system, which investigates the environment’s temperature and humidity effect on the bee activity and honey production of Heterotrigona Itama, a stingless bee species, is presented. The variables observed by the system are the weight of the honey container, the temperature inside the hive, humidity inside the hive, temperature of the environment outside of the hive, the humidity of the environment outside of the hive, and bee activity counter. The sensors used are Strain Gauge Load Cell (SGLC) sensor for weighing purposes, DHT22 sensors for temperature and humidity, and infrared transceivers bee counter sensor for bee activity monitoring. All installed sensors were controlled by using a NodeMCU microcontroller. All data were recorded and transferred to a Google Firebase real-time database. The proposed system offers an android application to access the recorded data called EMAS apps. EMAS fetches all the information from the database and represents it on graphs and pages in the user smart devices. This paper analyses the data obtained for 36 hours from a single hive. Results obtained represent a relationship between the temperature collected and bee activity with the honey produced. It was observed that in the morning, the increase of temperature leads to high traffic of bees going out of the hive, which decreases the weight of the hive to 2.7 Kg. Meanwhile, in the evening, the decrease in temperature leads to high traffic of bees going into the hive, which increases the hive weight to 4.5 Kg. For future work, to enhance the system’s performance, installation of the embedded system into an array of hives was advised and long- term data observation process was required. Keywords—Heterotrigona Itama, embedded system, android application I. INTRODUCTION Precision Beefarming (PB) is characterised as the apiary management technique, which depends on the observation of bee health state and increasing profitability [1]. The technique collects and analyses a current state of a hive and sends early warnings to beekeepers for immediate response. Temperature and humidity are the most critical variables in beehive monitoring. These variables can be used to evaluate the colony condition [2], colony health level [3], the bees’ queen condition, the respiration process in the hive, the level of the fungus growth on the interior walls of the hive [4], and the actual stage of Colony Collapse Disorder (CCD) [5]. There are three levels of data collection category. Firstly, the apiary level, secondly the colony level, and thirdly the individual bee level. The traditional monitoring system which utilizes direct human observation and intervention is too subjective and time consuming [6]. Moreover, the time span for data collection` is limited and irregular, which depends on weather conditions. Hence some important data might be lost during the observation process. Human health and safety are also at risk if overnight observation is required. However, relocating the beehive closer to human residential areas for easy monitoring can incite different kind of problems that originate from the surrounding. This include as attracting black soldier flies, predators to stingless bee as well as the fogging activities performed in these residential areas to control pests and insects [7]. Towards the industrial revolution 4.0, the ubiquity of advanced wireless sensor network and information technologies has been widely explored by researchers for collecting physical items in a system equipped with “Internet of Things (IoT)” [8]. Beehive monitoring which employed modern technologies and techniques had made significant progress in 2007 [9]. The applications utilizes invasive sensors that inevitably made contact with the inner part of the hives or bodies of the bees through the use of a thermocouple for hive temperature monitoring [9] and Radio-Frequency Identification (RFID) tags for bees foraging activity monitoring [10]. Utilizing these techniques, the respective hives need to be opened and exposed to the environment, hence causing discomfort and stress to the bee colony during the data collection, hence not favored in this research. However, in recent years, the non-invasive sensors have been heavily utilized that have the advantages of performing continuous monitoring remotely. The paramount importance of hive monitoring and data collections is to monitor the development status of the bee colony [11]. the collected data also is able to assist the beekeeper in predicting some unusual events such as swarming/pre-swarming [12], excessive honey spilt due to infestation of invaders [13], death and absence of queen bees [14], health and growth condition of the brood [15], dying or starving of the bee colony due to lack of food, and the low level of foraging activity [16]. Prompt actions from the 2021 IEEE International Conference in Power Engineering Application (ICPEA), 8-9 March 2021 978-1-7281-8546-0/21/$31.00 ©2021 IEEE 149 2021 IEEE International Conference in Power Engineering Application (ICPEA) | 978-1-7281-8546-0/21/$31.00 ©2021 IEEE | DOI: 10.1109/ICPEA51500.2021.9417758 Authorized licensed use limited to: UNIVERSITY TEKNOLOGI MALAYSIA. Downloaded on November 23,2021 at 04:15:20 UTC from IEEE Xplore. Restrictions apply.