Dr. Naveed Bhatti and his team of researchers at SBASSE have published their research in ACM SenSys 2025, an A* conference in the field of the Internet of Things (IoT). This year, the conference received 245 submissions, with only 46 accepted (an 18% acceptance rate) highlighting the competitive nature of the selection process.
Their work, CheckMate, introduces an automated framework that uses large language models (LLMs) to optimize energy efficiency in battery less IoT devices. By identifying areas where slight approximations can significantly reduce power consumption, CheckMate cuts power cycles by up to 60%, while keeping accuracy loss minimal. The framework streamlines a process that previously required manual fine-tuning, offering a more efficient approach to developing battery less systems.

What started as a CS 677 (Topics in IoT) course project in 2024 has now reached an international research platform. The project was led by Abdur Rehman and Abdullah Soomro, with contributions from Abdul Rafay. Abdur Rehman, the first author, is in his final semester at SBASSE LUMS. Abdullah Soomro is currently at UMass, while Abdul Rafay continues as a Teaching Fellow at LUMS.

The paper is available on arXiv, and the source code can be accessed here.