Edge Computing with Mobile Machines to Collect Field Data
Outcome/Accomplishment
Edge computing refers to processing, analyzing, and storing data closer to where it is generated to enable rapid, near real-time analysis and response. The application of edge computing using mobile machines to collect data in the field would be a major step forward in improving agricultural efficiency. Progress in this area is being pursued by researchers at the NSF-funded Internet of Things for Precision Agriculture (IoT4Ag) Engineering Research Center (ERC), headquartered at the University of Pennsylvania.
Impact/Benefits
This project aims to leverage wireless communications and machine-based edge computing for collecting data from a system operating across one or more fields. Machines travel throughout the farm and provide opportunities to connect large areas. Though mobile, these machines usually travel slowly. Additionally, the machines have sufficient power and space to support moderate-to-high power and large-sized electronics that can pre-process data and reduce the burden of field-to-cloud data transport over rural backhauls.
Explanation/Background
In 2022, an Avena software stack was released and new applications successfully leveraged its design. The iteration time during machine software development was reduced and, overall, the level of successful initial deployments increased.
Simulation of a Delay Tolerant Network (DTN), using location data collected with ISOBlue and using the hardware specifications of the machine-to-machine experiment, was achieved. The newly developed systems were demonstrated during the 2022 IoT4Ag Annual Meeting at Purdue, a Center partner institution.
Location
Philadelphia, Pennsylvaniawebsite
Start Year
Microelectronics and IT
Microelectronics, Sensing, and IT
Lead Institution
Core Partners
Fact Sheet
Outcome/Accomplishment
Edge computing refers to processing, analyzing, and storing data closer to where it is generated to enable rapid, near real-time analysis and response. The application of edge computing using mobile machines to collect data in the field would be a major step forward in improving agricultural efficiency. Progress in this area is being pursued by researchers at the NSF-funded Internet of Things for Precision Agriculture (IoT4Ag) Engineering Research Center (ERC), headquartered at the University of Pennsylvania.
Location
Philadelphia, Pennsylvaniawebsite
Start Year
Microelectronics and IT
Microelectronics, Sensing, and IT
Lead Institution
Core Partners
Fact Sheet
Impact/benefits
This project aims to leverage wireless communications and machine-based edge computing for collecting data from a system operating across one or more fields. Machines travel throughout the farm and provide opportunities to connect large areas. Though mobile, these machines usually travel slowly. Additionally, the machines have sufficient power and space to support moderate-to-high power and large-sized electronics that can pre-process data and reduce the burden of field-to-cloud data transport over rural backhauls.
Explanation/Background
In 2022, an Avena software stack was released and new applications successfully leveraged its design. The iteration time during machine software development was reduced and, overall, the level of successful initial deployments increased.
Simulation of a Delay Tolerant Network (DTN), using location data collected with ISOBlue and using the hardware specifications of the machine-to-machine experiment, was achieved. The newly developed systems were demonstrated during the 2022 IoT4Ag Annual Meeting at Purdue, a Center partner institution.