1 citations · 2 across the 6 of their papers we have counts for
6 papers
Ask for Any Appliance: A Prompt-Programmable Foundation Model for Non-Intrusive Load Monitoring
Xudong Wang, Jiacheng Cui, Junyu Xue +2
Non-intrusive load monitoring (NILM) estimates appliance-level consumption from a whole-home meter, but appliance-specific models and fixed output inventories make coverage costly…
ARTSN: Exact and Adaptive Self-triggered Traffic Scheduling for ARTS Networks
Ruide Cao, Shuangping Zhan, Jiashuo Lin +4
Autonomous real-time systems (ARTS), such as self-driving vehicles and robotic assembly lines, are increasingly deployed to improve efficiency, accuracy, and responsiveness with re…
SAGkit: A Python SAG Toolkit for Response Time Analysis of Hybrid-Triggered Jobs
Ruide Cao, Zhuyun Qi, Qinyang He +3
For distributed control systems, modern latency-critical applications are increasingly demanding real-time guarantees and robustness. Response-time analysis (RTA) is useful for thi…
Energy Injection Identification enabled Disaggregation with Deep Multi-Task Learning
Xudong Wang, Guoming Tang, Junyu Xue +3
Non-Intrusive Load Monitoring (NILM) offers a cost-effective method to obtain fine-grained appliance-level energy consumption in smart homes and building applications. However, the…
Prompting Large Language Models for Training-Free Non-Intrusive Load Monitoring
Junyu Xue, Xudong Wang, Xiaoling He +3
Non-intrusive load monitoring (NILM) aims to disaggregate total electricity consumption into individual appliance usage, thus enabling more effective energy management. While deep…
Towards Real-world Deployment of NILM Systems: Challenges and Practices
Junyu Xue, Yu Zhang, Xudong Wang +2
Non-intrusive load monitoring (NILM), as a key load monitoring technology, can much reduce the deployment cost of traditional power sensors. Previous research has largely focused o…