Beehive Key Parameters Online Monitoring System and Performance Test

doi:10.12133/j.smartag.2020.2.2.202004-SA001

Abstract

Abstract:

With the development of information technology, using big data analysis, monitoring of Internet of Things, sensor perception, wireless communication and other technologies to build a real-time online monitoring system for beehive is a feasible solution for reducing the stress response of bee colony caused by check the beehive artificially. Focusing on situation that real-time monitoring in the closed environment of the beehive is difficult, the STM32F103VBT6 32-bit microcontroller, integrated with the temperature and humidity sensor, microphone, and laser beam sensor were used in this study to develop a low-power, continuous working online monitoring system for the multi-parameter information acquisition and monitoring of beehive key parameters. The system mainly includes core processing module, data acquisition module, data sending module and database server. The data collection module includes a temperature and humidity collection unit inside the beehive, a bee colony sound collection unit, a bee in and out nest number counting unit, etc., and transfers data by accessing the mobile communication network. The performance test results of system on-site deployment showed that the developed system could monitor the temperature and humidity in the beehive in real time, effectively distinguish the bees of entering and leaving the beehive, record the numbers of bees of entering and leaving the nest door, and the bee colony sounds that the automatically obtained were consistent with the standard sound distribution of bee colony. The results indicate that this system meets the design requirements, can accurately and reliably collect the beehive parameters data, and can be used as a data collection method for related research of bee colony.

Key words: bee colony, STM32, online monitoring, sensor, agricultural Internet of Things

CLC Number:

TP311

YANG XuanJiang, LI Hualong, LI Miao, HU Zelin, LIAO Jianjun, LIU Xianwang, GUO Panpan, YUE Xudong. Beehive Key Parameters Online Monitoring System and Performance Test[J]. Smart Agriculture, 2020, 2(2): 115-125.

References

1	2018年中国蜜蜂养殖现状分析[EB/OL]. [2020-07-01]. .
2	何旭江, 曾志将. 蜜蜂生物学与饲养管理技术研究进展[J]. 蜜蜂杂志, 2019, 39(2): 9-12.
2	HE X, ZENG Z. The advance of honeybee biology and beekeeping technology[J]. Journal of Bee, 2019, 39(2): 9-12.
3	杨少婷, 周冰峰. 谈蜜蜂饲养管理技术的发展[J]. 中国养蜂, 2000(3): 15.
3	YANG S, ZHOU B. On the development of bee feeding and management technology[J]. Apiculture of China, 2000(3): 15.
4	唐明双. 无线传感器网络应用技术综述[J]. 科技资讯, 2018, 16(36): 42-43.
4	TANG M. Summary of wireless sensor network application technology[J]. Science & Technology Information, 2018, 16(36): 42-43.
5	MEIKLE W G, HOLST N. Application of continuous monitoring of honeybee colonies[J]. Apidologie, 2015, 46(1): 10-22.
6	CEJROWSKI T, SZYMANSKI J, MORA H, et al. Detection of the bee queen presence using sound analysis[C]// Asian Conference on Intelligent Information and Database Systems. Berlin, German: Springer, 2018: 297-306.
7	MURPHY F E, MAGNO M, WHELAN P, et al. B+ WSN: Smart beehive for agriculture, environmental, and honey bee health monitoring—Preliminary results and analysis[C]// Piscataway, New York, USA: IEEE, 2015: 1-6.
8	MURPHY F E, MAGNO M, OLEARY L, et al. Big brother for bees (3B)—Energy neutral platform for remote monitoring of beehive imagery and sound[C]// Piscataway, New York, USA: IEEE, 2015: 106-111.
9	Simon Fraser University. "Technology tracks 'bee talk' to help improve honey bee health."[N/OL]. ScienceDaily. [2020-07-02]. .
10	马德贵, 王飞, 王硕, 等. 养蜂箱内温湿度远程监测系统研究[J]. 安徽农业科学, 2008, 36(36): 16236-16237, 16260.
10	MA D, WANG F, WANG S, et al. Study on the remote monitoring system of temperature and humidity in beehives[J]. Journal of Anhui Agricultural Sciences, 2008, 36(36): 16236-16237, 16260.
11	谭庆忠. 蜜蜂蜂箱专用数字化监测系统设计与实现[D]. 长沙: 湖南大学, 2012.
11	TAN Q. Design and implementation of digital monitoring system special for beehive[D]. Changsha: Hunan University, 2012.
12	黄洪云. 一种基于自动温控系统的智能太阳能养蜂箱: CN106550906A[P]. 2017-04-05.
12	HUANG H. Intelligent solar beekeeping box based on automatic temperature control system: CN106550906A[P]. 2017-04-05.
13	柴秋子, 陈东晓, 余红, 等. 基于超低功耗单片机和光电传感器的蜜蜂计数监测系统设计[J]. 农业工程学报, 2017, 33(13): 193-198.
13	CHAI Q, CHEN D, YU H, et al. Design of monitoring and counting system for bee colony based on ultralow-power consumption MCU and photoelectric sensor[J]. Transactions of the CSAE, 2017, 33(13): 193-198.
14	张江毅, 陈丹红, 衣天宇. 基于物联网技术的智能蜂箱与智能蜂场的研究与开发[J]. 科学技术创新, 2019, 3: 102-103.
14	ZHANG J, CHEN D, YI T, et al. Research and development of intelligent beehive based on Internet of Things technology[J]. Scientific and Technological Innovation, 2019, 3: 102-103.
15	张晓青, 冯奇杰. 基于物联网技术的蜂箱管理系统[J]. 通讯世界, 2019, 26(12): 28-30.
15	ZHANG X, FENG Q. Beehive management system based on Internet of Things technology[J]. Telecom World, 2019, 26(12): 28-30.
16	ALGHAMDI A S H, GRAY A. Multivariate statistics for analysis of honey bee propolis[C]// Royal Statistical Society Conference 2017. Hoboken, New Jersey: John Wiley & Sons, Inc., 2017.
17	廖建军, 李淼, 李华龙, 等. 基于WSN的蜂群监测系统研制与性能测试[J]. 仪表技术, 2018(9): 1-5, 50.
17	LIAO J, LI M, LI H, et al. A WSN-based honeybee colony monitoring system and its performance[J]. Instrumentation Technology, 2018(9): 1-5, 50.
18	STABENTHEINER A, PRESSL H, PAPST T. Endothermic heatproductionin honeybee winter clusters[J]. Journal of Experimental Biology, 2003, 206(2): 353-358.
19	JIANG J A, WANG C H, CHEN C H, et al. A WSN-based automatic monitoring system for the foraging behavior of honey bees and environmental factors of beehives[J]. Computers and Electronics in Agriculture, 2016, 123: 304-318.
20	KVIESIS A, ZACEPINS A, RIDERS G. Honey bee colony monitoring with implemented decision support system[C]// 14th International Scientific Conference Engineering for Rural Development. Jelgava, Latvia: Latvia University of Agriculture, 2015: 20-22.
21	范春辉. 物联网短距离无线传输技术研究[J]. 无线互联科技, 2017, 10(19): 23-24.
21	FAN C. Study on short-range wireless transmission technology in Internet of Things[J]. Wireless Internet Technology, 2017, 10(19): 23-24.

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