Research

• Mobile Data Collection with Drones for Real-time Monitoring Tasks for Firefighting in High-rises & Wildland fires                                              Jun. 2019-present 

- Research on real-time monitoring to capture status of high-rise& wildland fires using a group of drones mounted with thermal cameras and sensors.

- Design of physics-inspired rule-based task generation procedure providing spatial-temporal sensing requirements for drones. 

- Design of a waypoint scheduling method for deciding the locations and orientations of drones for the monitoring task at hand when subjected to the data collection requirements and drone-safety.

- Design of the dynamic path scheduling mechanism for guiding multiple drones to monitoring specific areas with the consideration of prior-known 3-D building models and specific monitoring requirements.

• Network Planning for Mobile Data Collection from IoT Islands Using Public Transit                                                                                                                                                                        Sep. 2017- Feb. 2019 

- Proposed a data ferry routing mechanism for data collection from IoT islands in urban scenarios with the help of public transit. 

-  Proposed methods for deployment of upload points (UP) for data ferries in IoT islands 

to minimize the installation cost, while achieving application requirements. 

-  Leveraged the One Simulator to explore the effects of network parameters on the UP 

deployment, and the cost and utility of different UP deployment methods.

• Network Cross Layer Optimization for Data Transmission in VANET

Sep. 2017- May. 2018 

- Proposed an Application-driven Multi-hop Broadcast (ADMB) method for Vehicular Ad-Hoc Networks (VANETs) to address the tradeoff between application profit and net- work cost in deciding whether or not to relay the broadcast at each hop.

- Performed extensive numerical calculations, using Matlab, OMNET++ simulators, to investigate the applicability and utility of ADMB against various combinations of application requirements and network parameters.

• Consistency of Mobile Network in Distributed Cooperative Control 

Sep. 2016 - May. 2017

- Proposed a real-time and distance-driven consensus quantification model especially for C-ITS applications. This model encodes agents’ spatial location distribution into their mutual consensus quantification through introducing their inter-distance into consensus calculation. 

- Proposed a distance driven-consensus-based power adaptive control method based on the proposed consensus quantification scheme, which enables agents to make a real-time decision of transmit power through balancing the desired consensus and power cost.