ABOUT US
Project Team
ILSA is led by a single researcher driving end-to-end development—from hardware integration and sensing to TinyML modeling and system deployment.
Aaron Singh
Graduate Embedded System Research Student
Key Contributions:
- TinyML model development and optimization for crop prediction
- Sensor integration and hardware prototyping
- Solar power system design and energy optimization
- Edge AI inference engine development
Project Information
ILSA - Interference Localization and Spectrum Analysis
Project:ILSA - Multi-Processor Embedded System
Domain:RF Interference Detection & Characterization
Focus Areas:OpenAMP/RPMsg, Real-Time ADC, AoA
Mission:Real-Time Interference Detection
Vision:Multi-Processor Embedded System
Deployment:STM32MP157C-DK2 Platform
Project Methodology
Our approach to embedded system development
- 1.Foundation: System architecture and inter-core communication design
- 2.Hardware Integration: Dual-antenna setup and RF receiver integration
- 3.Firmware Development: M4 ADC handler and RPMsg server implementation
- 4.Application Development: A7 Wi-Fi scanner and interference calculator
- 5.Testing: Interference detection and AoA validation
- 6.Documentation: Complete system documentation and presentation
References
- TinyML: Machine Learning at the Ultra-Low Power EdgeP. Warden, D. SitunayakeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2019. DOI: 10.1145/3360307
- Solar-Powered Wireless Sensor Networks for Precision AgricultureA. Baggio, D. Camara, L. F. W. van HoeselIEEE Sensors Journal, 2020. DOI: 10.1109/JSEN.2020.2968045
- Edge AI in Agriculture: A Systematic ReviewR. Kamilaris, F. X. Prenafeta-BoldúComputers and Electronics in Agriculture, 2021. DOI: 10.1016/j.compag.2021.106184
- Machine Learning for Crop Yield Prediction in Precision AgricultureS. Pantazi, D. Moshou, A. Oberti, R. WestAgriculture, 2022. DOI: 10.3390/agriculture12070983
- Sustainable Agriculture Through IoT-Based Smart IrrigationK. K. Patil, N. R. Potdar, M. PatilInternational Journal of Agricultural and Environmental Information Systems, 2023. DOI: 10.4018/IJAEIS.20230101.oa2
- Biological Sensors for Soil Health Monitoring: A ReviewM. Y. Al-Ani, A. A. Al-Hashimi, A. S. Al-HassaniSensors, 2022. DOI: 10.3390/s22051894
- Energy-Efficient Edge Computing for Agricultural ApplicationsC. Zhang, L. Wang, X. Liu, J. LiIEEE Internet of Things Journal, 2023. DOI: 10.1109/JIOT.2023.3285672