Demo Data from EDBT 2026 / reviewers in the wild / expert
Kooklae Jo
dblp:10/10522
· DBLP profile ↗
4ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 4
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
4 papers |
Internet of things and sensor networks · 69% Wireless sensing and localization · 31% | |
| Interdisciplinary, comprehensive, and emerging computing
2 papers |
Environmental and earth informatics · 54% Energy systems and smart grids · 46% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% |
Topics — the 5 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Environmental and earth informatics
environmental monitoring |
0.2 | 1 | 2013 | High-fidelity environmental monitoring using wireless sensor networks · SenSys 2013 |
Energy systems and smart grids › energy management
energy monitoring |
0.1 | 1 | 2012 | PEAKSAVE: energy monitoring service · SenSys 2012 |
Internet of things and sensor networks › wireless sensor network
wireless sensor nodes |
0.1 | 1 | 2012 | Modular approach in sensor board design · SenSys 2012 |
Internet of things and sensor networks
wireless sensor network |
0.1 | 3 | 2013 | High-fidelity environmental monitoring using wireless sensor networks · SenSys 2013 PEAKSAVE: energy monitoring service · SenSys 2012 Tracking vehicles in a container terminal · SenSys 2011 |
Wireless sensing and localization › tracking › RF tracking
RSSI-based tracking |
0.1 | 1 | 2011 | Tracking vehicles in a container terminal · SenSys 2011 |
Methods — techniques the papers use, named apart from their topics
wireless sensor network · 0.6modular design · 0.3filtering · 0.1RSSI · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | High-fidelity environmental monitoring using wireless sensor networksabstractThe system is environment monitoring service based on Wireless Sensor Networks (WSN). Users can know temperature, humidity, light, and CO2 level in real time. Excessive electricity consumption by lighting in the office can be saved and the quality of the office environment can become better by controlling lighting and CO2 level. Jeonghoon Kang, Su Chang Lee, Sukun Kim, David E. Culler, Pil-Mhan Jung, Taejoon Choi, Kooklae Jo, JaeYeol Shim |
SenSys | 8 |
| 2012 | Modular approach in sensor board designabstractDesigning a new sensor board is costly, especially for a production in a small quantity. By modularizing common functionalities, a large portion of the sensor board can be reused. In this work, we propose an Extension Board, a sensor board which is modularized into 3 parts. Power module, and MCU and RF module are shared, and only sensing module is redesigned for each sensor board. Diverse sensing modules are produced. The process was simple and inexpensive. Jeonghoon Kang, Jaechul Kim, Du-Hwan Yeo, Jongmin Hyun, Kooklae Jo, Taejoon Choi, Pil-Mhan Jung, Su Chang Lee, Sukun Kim |
SenSys | 5 |
| 2012 | PEAKSAVE: energy monitoring serviceabstractPEAKSAVE system is an energy monitoring service based on Wireless Sensor Networks (WSN). A smartphone is an important point of a system. Users can understand the energy consumption of each electric device and lighting in real time. Responsive energy monitoring service can help in reducing the waste of energy, especially in shaving electric load in a peak time. Jeonghoon Kang, Jaechul Kim, Du-Hwan Yeo, Jongmin Hyun, Pil-Mhan Jung, Taejoon Choi, Kooklae Jo, Su Chang Lee, Sukun Kim |
SenSys | 7 |
| 2011 | Tracking vehicles in a container terminalabstractVehicle tracking system is built for a container terminal. In the system, reference nodes are fixed at known locations. They provide reference locations to a mobile node, which is installed in a vehicle. Received Signal Strength Indicator (RSSI) is measured, and the measured data is gathered in a backend server. The backend server analyzes the data, and estimates the location of the mobile node. Filters are added to handle transient fluctuation in RF environment. SonnoOne mote is made to be used as a mobile node. It contains MG2455 chip from RadioPulse, which combines 8051 MCU and IEEE 802.15.4 radio. We expect the cost will be below $20, and the low cost will enable a large number of mobile nodes to be deployed in a container terminal. Jeonghoon Kang, Jongmin Hyun, Dongik Kim, Kooklae Jo, Pil Mhan Jeong, Taejoon Choi, Sukun Kim |
SenSys | 4 |