Jiang, Zhihao, Abbas, Houssam, and Jang, Kuk Jin, Beccani, Marco, Liang, Jackson, Dixit, Sanjay, Mangharam, Rahul.
2016.
In-silico pre-clinical trials for implantable cardioverter defibrillators. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). :169-172.
Mangharam, Rahul, Abbas, Houssam, Behl, Madhur, Jang, Kuk Jin Pajic, Miroslav, Jiang, Zhihao.
2016.
Three challenges in cyber-physical systems. 2016 8th International Conference on Communication Systems and Networks (COMSNETS). :1-8.
Abbas, Houssam, Jiang, Zhihao, Jang, Kuk Jin, Beccani, Marco, Liang, Jackson, Dixit, Sanjay, Mangharam, Rahul.
2016.
High-Level Modeling for Computer-Aided Clinical Trials of Medical Devices. IEEE International High Level Design Validation and Test Workshop (HLDVT). :85-92.
Balasubramani, Booma Sowkarthiga, Belingheri, Omar, Boria, Eric S., Cruz, Isabel F., Derrible, Sybil, Siciliano, Michael D..
2017.
GUIDES -– Geospatial Urban Infrastructure Data Engineering Solutions (Demo Paper). {To appear in Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems}.
Faria, Daniel, Pesquita, Catia, Balasubramani, Booma S, Martins, Catarina, Cardoso, Joao, Curado, Hugo, Couto, Francisco M, Cruz, Isabel F.
2016.
OAEI 2016 results of AML. {ISWC International Workshop on Ontology Matching (OM)}. 1766:138–145.
L. Vacek, E. Atter, P. Rizo, B. Nam, R. Kortvelesy, D. Kaufman, J. Das, V. Kumar.
2017.
sUAS for Deployment and Recovery of an Environmental Sensor Probe. IEEE International Conference on Unmanned Aircraft Systems (ICUAS) 2017.
Small Unmanned Aircraft Systems (sUAS) are already revolutionizing agricultural and environmental monitoring through the acquisition of high-resolution multi-spectral imagery on-demand. However, in order to accurately understand various complex environmental and agricultural processes, it is often necessary to collect physical samples of pests, pathogens, and insects from the field for ex-situ analysis. In this paper, we describe a sUAS for autonomous deployment and recovery of a novel environmental sensor probe. We present the UAS software and hardware stack, and a probe design that can be adapted to collect a variety of environmental samples and can be transported autonomously for off-site analysis. Our team participated in an NSF-sponsored student unmanned aerial vehicle (UAV) challenge, where we used our sUAS to deploy and recover a scale-model mosquito trap outdoors. Results from indoor and field trials are presented, and the challenges experienced in detecting and docking with the probe in outdoor conditions are discussed.