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IoTDI 2020
5th ACM/IEEE Conference on Internet of Things Design and Implementation
April 21-24, 2020 — Sydney, Australia
Accepted Papers
REACT: an Agile Control Plane for Industrial Wireless Sensor-Actuator Networks
RepEL: A Utility-preserving Privacy System for IoT-based Energy Meters
Recovery-Conscious Adaptive Watermark Determination Technique to Achieve Low Latency in Time-Order Event Stream Processing
Leveraging Fine-Grained Occupancy Estimation Patterns for Effective HVAC Control
QID: Identifying Mobile Devices via Wireless Charging Fingerprints
Learning Context-aware Policies from Multiple Smart Homes via Federated Multi-Task Learning
The Standby Energy of Smart Devices: Problems, Progress, & Potential
LinkLab: A Scalable and Heterogeneous Testbed for Remotely Developing and Experimenting IoT Applications
Evaluating Emergency Evacuation Events Using Building WiFi Data
MapTransfer: Urban Air Quality Map Generation for Downscaled Sensor Deployments
Towards IoT Device Identification in the Wild
Characterizing Smart Home IoT Traffic in the Wild
SPIDERS: Low-Cost Wireless Glasses for Continuous In-Situ Bio-Signal Acquisition and Emotion Recognition
IDIoT: Towards Ubiquitous Identification of IoT Devices through Visual and Inertial Orientation Matching During Human Activity
Short Papers
Adaptive Data Replication in Real-Time Reliable Edge Computing for Internet of Things
Recorp: Receiver-Oriented Policies for Industrial Wireless Networks
IoTRepair: Systematically Addressing Device Faults in Commodity IoT
OAC: Overlapping Office Activity Classification through IoT-Sensed Structural Vibration
ECCO: Edge-Cloud Chaining and Orchestration Framework for Road Context Assessment
DevLoc: Seamless Device Association using Light Bulb Networks for Indoor IoT Environments
Time Awareness in Deep Learning-Based Multimodal Fusion Across Smartphone Platforms
A Battery-Free In-Class Response System using RFID Tags
A Novel Data Collection Framework for Telemetry and Anomaly Detection in Industrial IoT Systems
Fast and Accurate Streaming CNN Inference via Communication Compression on the Edge