Demo Data from EDBT 2026 / reviewers in the wild / expert
Jacob Palmer
dblp:164/8370
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Internet of things and sensor networks · 64% Physical-layer communications · 28% Vehicular, aerial and satellite networks · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Physical-layer communications › optical wireless communication
air-water communication |
0.2 | 1 | 2015 | On air-to-water radio communication between UAVs and water sensor networks · ICRA 2015 |
Internet of things and sensor networks › wireless sensor network
sensor deployment |
0.2 | 1 | 2015 | On air-to-water radio communication between UAVs and water sensor networks · ICRA 2015 |
Internet of things and sensor networks
underwater sensor networks |
0.2 | 1 | 2015 | On air-to-water radio communication between UAVs and water sensor networks · ICRA 2015 |
Internet of things and sensor networks › delay tolerant networks
data muling |
0.1 | 1 | 2015 | On air-to-water radio communication between UAVs and water sensor networks · ICRA 2015 |
Vehicular, aerial and satellite networks
UAV communication |
0.1 | 1 | 2015 | On air-to-water radio communication between UAVs and water sensor networks · ICRA 2015 |
Methods — techniques the papers use, named apart from their topics
field experiments · 0.2energy analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | On air-to-water radio communication between UAVs and water sensor networksabstractOcean monitoring using underwater sensor networks faces communication challenges in retrieving data, communicating large amounts of data between nodes, and covering increasing spatial regions while remaining connected. With underwater sensor networks that are capable of surfacing, unmanned aerial vehicles (UAVs) provide a solution to this by providing radio-based data muling services, but, as this area is still unexplored, the utility of this solution is unclear. In this paper, we examine the theoretical expectations, perform several field experiments, and analyze the communication success rates of 802.15.4 radios near the water surface both communicating between surface nodes as well as between a node and the UAV. These indicate that on the water surface internode radio communication is poor, but node to UAV communication can provide both reasonable ranges and success rates. We additionally measure and analyze the energy aspects of the systems, determining the impacts of parameters such as network size and distance between nodes on the UAV energy. Finally, we consolidate the information into an algorithm outlining how to configure and design hybrid UAV and underwater sensor network systems. Jacob Palmer, Nicholas Yuen, John-Paul Ore, Carrick Detweiler, Elizabeth Basha |
ICRA | 1 |