Abstract & Details
Description
Award ID: 2321317
This Small Business Innovation Research (SBIR) Phase I proposal is making online and digital interactions safer for children between the ages of 10 14 years of age by using artificial intelligence technology to monitor text communication and inform their parents of potential danger in real-time. Youth aged 10 14 years are particularly vulnerable to the risks of online activity since they are newcomers to the metaverse and they are likely getting a personal communication device for the first time. Parents want their kids to have the freedom and privacy to use their devices but fear the risks involved. This project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger (e.g., online predation, cyberbullying, and/or school violence) or risky behaviors (e.g., drug and alcohol use, and/or self-harm), so parents can intervene to protect their child. The app will provide an attractive alternative to existing products on the market because of its sophisticated artificial intelligence engine and because it does not collect and transfer all the phones data the solution reduces the risk of data leaks while still keeping parents informed. This Small Business Innovation Research (SBIR) Phase I project is advancing the state of artificial intelligence and machine learning technologies by developing a detection algorithm that runs entirely on a mobile device and is tailored to the users activity. Unlike large language models, which are general and wide-ranging, and thus require a lot of computing at a central server, this technology will have a small footprint and be personalized and adapted for each family. Throughout this project, the team will collect and label textual communication directly from youth and use the data to improve the algorithms accuracy, as measured by precision and recall. The project team will also develop the technology to collect and process the data on popular models of cell phones and to alert the parent when needed. The project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger or risky behaviors, so they can act proactively to protect their children from harm. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Parvathi Chundi
This Small Business Innovation Research (SBIR) Phase I proposal is making online and digital interactions safer for children between the ages of 10 14 years of age by using artificial intelligence technology to monitor text communication and inform their parents of potential danger in real-time. Youth aged 10 14 years are particularly vulnerable to the risks of online activity since they are newcomers to the metaverse and they are likely getting a personal communication device for the first time. Parents want their kids to have the freedom and privacy to use their devices but fear the risks involved. This project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger (e.g., online predation, cyberbullying, and/or school violence) or risky behaviors (e.g., drug and alcohol use, and/or self-harm), so parents can intervene to protect their child. The app will provide an attractive alternative to existing products on the market because of its sophisticated artificial intelligence engine and because it does not collect and transfer all the phones data the solution reduces the risk of data leaks while still keeping parents informed. This Small Business Innovation Research (SBIR) Phase I project is advancing the state of artificial intelligence and machine learning technologies by developing a detection algorithm that runs entirely on a mobile device and is tailored to the users activity. Unlike large language models, which are general and wide-ranging, and thus require a lot of computing at a central server, this technology will have a small footprint and be personalized and adapted for each family. Throughout this project, the team will collect and label textual communication directly from youth and use the data to improve the algorithms accuracy, as measured by precision and recall. The project team will also develop the technology to collect and process the data on popular models of cell phones and to alert the parent when needed. The project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger or risky behaviors, so they can act proactively to protect their children from harm. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Parvathi Chundi
| Status | Closed |
|---|---|
| Effective start/end date | 11/15/23 → 02/28/25 |
Funding
- SBIR Phase I: $274,996.00
Active Fiscal Year
- FY2024
- FY2025
Start Fiscal Year
- FY2024
TIP Programs
- SBIR Phase I
Small Business
- Yes
Key Technology Areas
- Artificial Intelligence
- (confidence score: 99%)
- Data and Cybersecurity
- (confidence score: 100%)
Technology Foci
- Data Privacy
- (confidence score: 99%)
- Bio-metrics
- (confidence score: 92%)
- Machine Learning Training Data
- (confidence score: 83%)
Congressional District at Award
- District n. 03 of Maryland
Current Congressional District
- District n. 03 of Maryland
United States
- Maryland
Core Based Statistical Area (CBSA)
- Baltimore-Columbia-Towson, MD
County
- County: Anne Arundel, MD
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine