System design for inferring colony-level pollination activity through miniature bee-mounted sensors

Abstract In digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we pre...

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Autores principales:	Haron M. Abdel-Raziq, Daniel M. Palmer, Phoebe A. Koenig, Alyosha C. Molnar, Kirstin H. Petersen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/37aeb7b418dc4529a078e2a194dbafc0
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spelling	oai:doaj.org-article:37aeb7b418dc4529a078e2a194dbafc02021-12-02T10:54:14ZSystem design for inferring colony-level pollination activity through miniature bee-mounted sensors10.1038/s41598-021-82537-12045-2322https://doaj.org/article/37aeb7b418dc4529a078e2a194dbafc02021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82537-1https://doaj.org/toc/2045-2322Abstract In digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems.Haron M. Abdel-RaziqDaniel M. PalmerPhoebe A. KoenigAlyosha C. MolnarKirstin H. PetersenNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Haron M. Abdel-Raziq Daniel M. Palmer Phoebe A. Koenig Alyosha C. Molnar Kirstin H. Petersen System design for inferring colony-level pollination activity through miniature bee-mounted sensors
description	Abstract In digital agriculture, large-scale data acquisition and analysis can improve farm management by allowing growers to constantly monitor the state of a field. Deploying large autonomous robot teams to navigate and monitor cluttered environments, however, is difficult and costly. Here, we present methods that would allow us to leverage managed colonies of honey bees equipped with miniature flight recorders to monitor orchard pollination activity. Tracking honey bee flights can inform estimates of crop pollination, allowing growers to improve yield and resource allocation. Honey bees are adept at maneuvering complex environments and collectively pool information about nectar and pollen sources through thousands of daily flights. Additionally, colonies are present in orchards before and during bloom for many crops, as growers often rent hives to ensure successful pollination. We characterize existing Angle-Sensitive Pixels (ASPs) for use in flight recorders and calculate memory and resolution trade-offs. We further integrate ASP data into a colony foraging simulator and show how large numbers of flights refine system accuracy, using methods from robotic mapping literature. Our results indicate promising potential for such agricultural monitoring, where we leverage the superiority of social insects to sense the physical world, while providing data acquisition on par with explicitly engineered systems.
format	article
author	Haron M. Abdel-Raziq Daniel M. Palmer Phoebe A. Koenig Alyosha C. Molnar Kirstin H. Petersen
author_facet	Haron M. Abdel-Raziq Daniel M. Palmer Phoebe A. Koenig Alyosha C. Molnar Kirstin H. Petersen
author_sort	Haron M. Abdel-Raziq
title	System design for inferring colony-level pollination activity through miniature bee-mounted sensors
title_short	System design for inferring colony-level pollination activity through miniature bee-mounted sensors
title_full	System design for inferring colony-level pollination activity through miniature bee-mounted sensors
title_fullStr	System design for inferring colony-level pollination activity through miniature bee-mounted sensors
title_full_unstemmed	System design for inferring colony-level pollination activity through miniature bee-mounted sensors
title_sort	system design for inferring colony-level pollination activity through miniature bee-mounted sensors
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/37aeb7b418dc4529a078e2a194dbafc0
work_keys_str_mv	AT haronmabdelraziq systemdesignforinferringcolonylevelpollinationactivitythroughminiaturebeemountedsensors AT danielmpalmer systemdesignforinferringcolonylevelpollinationactivitythroughminiaturebeemountedsensors AT phoebeakoenig systemdesignforinferringcolonylevelpollinationactivitythroughminiaturebeemountedsensors AT alyoshacmolnar systemdesignforinferringcolonylevelpollinationactivitythroughminiaturebeemountedsensors AT kirstinhpetersen systemdesignforinferringcolonylevelpollinationactivitythroughminiaturebeemountedsensors
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System design for inferring colony-level pollination activity through miniature bee-mounted sensors

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