research-article

HiveSpy

Author:

Navid ShaghaghiAuthors Info & Claims

GoodTechs '19: Proceedings of the 5th EAI International Conference on Smart Objects and Technologies for Social Good

Pages 126 - 127

https://doi.org/10.1145/3342428.3342677

Published: 25 September 2019 Publication History

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Abstract

Beekeeping is a labor intensive job which requires the daily inspection of every frame of every hive in an apiary. Apiaries are easily scalable via the addition of new hives or the expansion of existing hives but human labor cannot so easily be scaled to meet the added need as human labor is costly, often political, and time consuming. HiveSpy is a proposed and under research and development automated Internet of Things (IoT) solution for monitoring and reporting the weight of every frame of a hive effectively, efficiently, and remotely. Existing beekeeping and monitoring systems on the market are very costly and do not provide per-frame information to their users. Thus, although they are successful in generating a slew of useful information regarding the health, status, and even overall yields of a hive, they fall short in enabling beekeepers the luxury of only inspecting and harvesting the frames that are ready. As a result, the existing systems do not contribute to harvest related labor reduction nor are as effective as HiveSpy in the prevention of swarming.

References

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Richard Jones and Sharon Sweeney-Lynch. 2011. The Beekeeper's Bible. Stewart, Tabori and Chang.

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Douglas Santiago Kridi, Carlos Giovanni Nunes de Carvalho, and Danielo Gonçalves Gomes. 2014. A predictive algorithm for mitigate swarming bees through proactive monitoring via wireless sensor networks. In Proceedings of the 11th ACM symposium on Performance evaluation of wireless ad hoc, sensor, & ubiquitous networks. ACM, 41--47.

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Cited By

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Agrawal RSharma MShaghaghi N(2023)GrapeSense: A Comparative Study of Residual Transfer Learning Models for Grape Aging Classification Using Drone Images2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)10.1109/CSDE59766.2023.10487704(1-7)Online publication date: 4-Dec-2023
https://doi.org/10.1109/CSDE59766.2023.10487704
Shaghaghi NFerguson PGraham AMayer J(2023)Hydration Automation (HA): Smart TankProceedings of Eighth International Congress on Information and Communication Technology10.1007/978-981-99-3043-2_34(435-453)Online publication date: 1-Sep-2023
https://doi.org/10.1007/978-981-99-3043-2_34
Shaghaghi NCameron ZKniveton NMayer JTuttle WFerguson P(2020)ÂB: An Energy Aware Communications Protocol (EACP) for the Internet of Things (IoT)Web, Artificial Intelligence and Network Applications10.1007/978-3-030-44038-1_80(877-889)Online publication date: 31-Mar-2020
https://doi.org/10.1007/978-3-030-44038-1_80

Index Terms

HiveSpy
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Sensor applications and deployments
    2. Sensors and actuators
  2. Power and energy
    1. Impact on the environment
2. Social and professional topics
  1. Professional topics
    1. Computing and business
      1. Automation

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Published In

GoodTechs '19: Proceedings of the 5th EAI International Conference on Smart Objects and Technologies for Social Good

September 2019

272 pages

ISBN:9781450362610

DOI:10.1145/3342428

General Chairs:
Armir Bujari
Università di Padova, Italy
,
Pietro Manzoni
Universitat Politecnica de Valencia, Spain
,
Program Chairs:
Anna Forster
University of Bremen, Germany
,
Edjair Mota
UFAM, Brazil
,
Ombretta Gaggi
Università di Padova, Italy

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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EAI: The European Alliance for Innovation

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 September 2019

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GoodTechs '19

GoodTechs '19: EAI International Conference on Smart Objects and Technologies for Social Good

September 25 - 27, 2019

Valencia, Spain

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Cited By

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Agrawal RSharma MShaghaghi N(2023)GrapeSense: A Comparative Study of Residual Transfer Learning Models for Grape Aging Classification Using Drone Images2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)10.1109/CSDE59766.2023.10487704(1-7)Online publication date: 4-Dec-2023
https://doi.org/10.1109/CSDE59766.2023.10487704
Shaghaghi NFerguson PGraham AMayer J(2023)Hydration Automation (HA): Smart TankProceedings of Eighth International Congress on Information and Communication Technology10.1007/978-981-99-3043-2_34(435-453)Online publication date: 1-Sep-2023
https://doi.org/10.1007/978-981-99-3043-2_34
Shaghaghi NCameron ZKniveton NMayer JTuttle WFerguson P(2020)ÂB: An Energy Aware Communications Protocol (EACP) for the Internet of Things (IoT)Web, Artificial Intelligence and Network Applications10.1007/978-3-030-44038-1_80(877-889)Online publication date: 31-Mar-2020
https://doi.org/10.1007/978-3-030-44038-1_80

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Recommendations

Monitoring of swarming sounds in bee hives for early detection of the swarming period

Integrating machine learning and IoT into apiary management to optimize bee health and production

Analysis of Big Data technologies for use in agro-environmental science