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Chia-Min Su

dblp:179/3259 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 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
2 papers
Wireless sensing and localization · 53% Internet of things and sensor networks · 47%
Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › LPWAN
lora
0.312017
A LoRa wireless smart badge for enhancing museum visitors' experience: demo abstract · IPSN 2017
Wireless sensing and localization
indoor localization
0.212016
Poster Abstract: Exploiting Temporal Variation of Received Radio Signal Strength for Indoor Human Tracking · IPSN 2016
Collaborative and social computing
museum experience
0.112017
A LoRa wireless smart badge for enhancing museum visitors' experience: demo abstract · IPSN 2017
Wireless sensing and localization
bluetooth beacon
0.112016
Poster Abstract: Exploiting Temporal Variation of Received Radio Signal Strength for Indoor Human Tracking · IPSN 2016

Methods — techniques the papers use, named apart from their topics

lora · 0.3LoRA · 0.3radio fingerprinting · 0.2
YearPublicationVenuePosition
2017 A LoRa wireless smart badge for enhancing museum visitors' experience: demo abstract
abstract
This paper presents a smart badge system for managing museum visitors and improving their viewing experience. The badge uses a LoRa wireless interface for two-way long-distance communication with tour guides and the museum's control center. The control center can collect information such as the visitors' viewing p, location, and status of activity level, enabling it to wirelessly send suggestions of exhibits and visiting paths to visitors, avoiding the overcrowding of visitors in one location. Meanwhile, visitors can communicate with the control center to update their locations and ask simple questions via the badge. In this paper, we introduce the system architecture and the prototype smart badge that we used to evaluate the performance of this system.
Chia-Min Su, Cheng-Yu Shi, Yong-Lin Wu, Warren Huang-Chen Lee
IPSN1
2016 Poster Abstract: Exploiting Temporal Variation of Received Radio Signal Strength for Indoor Human Tracking
abstract
Indoor positioning is one of the key technologies for enabling location-aware applications. To the best of our knowledge, existing indoor positioning technologies are aimed at providing very high-accuracy location information, but are hindered by the need of a infrastructure with high installation and maintenance costs. In addition, their accuracy is usually highly variable and vulnerable to environmental changes or external interference. Thus, for applications of indoor human tracking, the practical considerations of choosing a suitable indoor positioning technique should be to provide adequate accuracy while also being economical. Based on this observation, our study presents an indoor, room-level tracking method characterized by an infrastructure with low costs to build and maintain. The user carries a mobile device that can determine his/her location with the help of Bluetooth beacons installed at the intersections between rooms and hallways. In contrast to traditional radio-fingerprint map and proximity approaches, in this study the mobile device tracks the user's moving direction and the temporal variation of the radio signal strength from nearby Bluetooth beacons, to determine when the device enters or leaves a given room or hallway. Therefore, by determining the sequence of a user's movements, his/her moving path can be recorded for indoor tracking or navigation.
Tzu-Ting Lin, Chun-Ju Lin, Chia-Min Su, Yi-Chun Lin, Warren Huang-Chen Lee
IPSN3