Overall Rating | Gold - expired |
---|---|
Overall Score | 65.20 |
Liaison | Olivia Conner-Bennett |
Submission Date | March 2, 2020 |
Stevens Institute of Technology
IN-47: Innovation A
Status | Score | Responsible Party |
---|---|---|
0.50 / 0.50 |
Dibs
Sarkar Professor Civil Environmental and Ocean Engineering |
"---"
indicates that no data was submitted for this field
Name or title of the innovative policy, practice, program, or outcome:
AI-Driven Pest Control
A brief description of the innovative policy, practice, program, or outcome that outlines how credit criteria are met and any positive measurable outcomes associated with the innovation:
Non-native pests are a scourge to forests that are valuable to industry and ecosystems. Stevens researchers in the Stevens Sensor Technology & Applied Research (STAR) Center developed and tested new technology that combines highly-sensitive vibration sensors, vibro-acoustic insect libraries and artificial intelligence to root out the dangerous pests hidden inside trees. Not only is the solution cost-effective and portable compared to other pest detection tools and techniques, but it can also identify the presence of pests before damage is even visually apparent on the surface of a tree, which will help limit the spread and protect more forest.
The Stevens team has applied for a patent on the technology and will continue to refine its system and signal processing algorithms, even as the modified system continues to undergo intensive testing in New Jersey parks.
The Stevens team has applied for a patent on the technology and will continue to refine its system and signal processing algorithms, even as the modified system continues to undergo intensive testing in New Jersey parks.
A letter of affirmation from an individual with relevant expertise or a press release or publication featuring the innovation :
---
The website URL where information about the innovation is available :
Additional documentation to support the submission:
---
Data source(s) and notes about the submission:
---
The information presented here is self-reported. While AASHE staff review portions of all STARS reports and institutions are welcome to seek additional forms of review, the data in STARS reports are not verified by AASHE. If you believe any of this information is erroneous or inconsistent with credit criteria, please review the process for inquiring about the information reported by an institution or simply email your inquiry to stars@aashe.org.