Recent papers on Resource Constrained Device Deployment

Sorted by publication year (newest first) via OpenAlex. List regenerates every 24h.

1. EdgeDistill: A Knowledge Distillation Approach for Deploying Large Language Models on Resource-Constrained Edge Devices in Industrial IoT

   2026 · Ingegneria Sismica · Chen, Changan

   2026

2. Edge AI: Deploying Machine Learning Models on Resource-Constrained Devices

   2026 · International Scientific Journal of Engineering and Management · Sohini, Sangoju Venkata Sri Lakshmi, Kumar, Modugu Dileep

   2026

3. From Federated Learning to Real-Time Pneumonia Prediction: Deploying an AdaptiveMesh-Based Global Model on Resource-Constrained Devices

   2026 · International Journal of Interactive Mobile Technologies (iJIM) · Shkurti, Lamir, Susuri, Arsim, Sofiu, Vehebi et al.

   2026

4. Enabling Edge Intelligence: A Quantum-Inspired Approach to Deploying AI Models on Resource-Constrained Devices

   2026 · S, Saravana Kumar C, Abhijeet, Rane, V, Mohan B et al.

   2026

5. Large Language Model Deployment on Resource-Constrained Edge Devices: A Practitioner's Survey

   2026 · Maliakkal, Rahul, Makin, Yashasvi, Rath, Plawan Kumar et al.

   2026

6. P-ML: An End-to-End AutoML Framework for Deploying Classical Machine Learning Models on Resource-Constrained Devices

   2026 · Zenodo (CERN European Organization for Nuclear Research) · Nguyen, Huu-Phuoc

   2026

7. SlimEdge: Performance and Device Aware Distributed DNN Deployment on Resource-Constrained Edge Hardware

   2025 · arXiv (Cornell University) · Kumar, Mahadev Sunil, Raha, Arnab, Das, Debayan et al.

   2025

8. Toward Efficient Deployment of Lightweight Object Detectors for Real-Time Inference on Resource-Constrained Edge Devices

   2025 · Taing, Thaising, Khan, Yousufzai Fawad, Aliev, Hayotjon et al.

   2025

9. Evaluation, optimization and deployment of convolutional computer vision models on resource-constrained devices

   2025 · UCrea (University of Cantabria) · Álvaro, Revuelta Burgos,

   2025

10. Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices

    2025 · ACM Transactions on Design Automation of Electronic Systems · Qin, Ruiyang, Liu, Dancheng, Xu, Chenhui et al.

    2025

11. Efficient Deployment of Large Language Models on Resource-constrained Devices

    2025 · arXiv (Cornell University) · Zhiwei, Yao,, Xu, Yang, Xu, Hongli et al.

    2025

12. Design and Evaluation of Cryptographic Protocols for Resource-Constrained IoT Devices: A Comparative Study of Lightweight and Post-Quantum Algorithms with Hybrid Deployment Models

    2025 · Taj Al-Ma rifa journal · Othman, Enas Saad

    2025

13. Deploying Emotion Recognition on Resource Constrained Device: Utilizing Light Weight Deep Learning Models with Multi-Physiological Signals

    2024 · Chen, Xu, Liang, Dong, Zhang, Jianwei et al.

    2024

14. TinyML for Cybersecurity: Deploying Optimized Deep Learning Models for On-Device Threat Detection on Resource-Constrained Devices

    2024 · Arcot, Sonali, Masum, Mohammad, Kader, Mohammad Shahidul et al.

    2024

15. Edge AI: Optimizing Machine Learning Models for Deployment on Resource-Constrained IoT Devices

    2024 · Nanotechnology Perceptions

    2024

16. An Empirical Study of Model Compression Techniques for DNN Deployment on Resource-Constrained Devices

    2024 · Lecture notes in networks and systems · More, Shraddha Subhash, Bansode, Rajesh

    2024

17. Deploying Machine Learning in Resource-Constrained Devices for Human Activity Recognition

    2023 · Reusch, Rafael Schild, Juracy, Leonardo Rezende, Moraes, Fernando Gehm

    2023

18. Deploying artificial intelligence in resource-constrained devices for human activity recognition

    2023 · Reusch, Rafael Schild

    2023

19. Challenges in Resource-Constrained IoT Devices: Energy and Communication as Critical Success Factors for Future IoT Deployment

    2020 · Sensors · Pereira, Felisberto, Correia, Ricardo, Pinho, Pedro et al.

    2020

20. Evaluation and Deployment of Resource-Constrained Machine Learning on Embedded Devices

    2020 · Repository for Publications and Research Data (ETH Zurich) · Heim, Lennart

    2020

21. Deploy Large-Scale Deep Neural Networks in Resource Constrained IoT Devices with Local Quantization Region

    2018 · arXiv (Cornell University) · Yang, Yi, Chen, Andy, Xiaoming, Chen, et al.

    2018

22. Manage resource-constrained IoT devices through dynamically generated and deployed YANG models

    2017 · Scheffler, Thomas, Bonneß, Olaf

    2017

23. Runtime Deployment Adaptation for Resource Constrained Devices

    2007 · Hens, Raf, Boone, Bas, Turck, Filip De et al.

    2007

24. Lightweight and Real-Time Object Detection on Edge Devices: A Unified Framework for Resource-Constrained Environments

    2026 · EAI endorsed transactions on intelligent systems and machine learning applications. · Zangana, Hewa Majeed

    2026

25. Federated sparse-learning framework for detecting low-rate stealth attacks in resource-constrained IoT devices

    2026 · Scientific Reports · Anandhi, R., Srikanth, G. Umarani

    2026

26. Author Correction: Dynamic Kannada sign language recognition on resource constrained devices

    2026 · Scientific Reports · Venkatappa, Umadevi, S, Nishanth K, S, Navneeth K et al.

    2026

27. LiteKV: A KV cache compression method for efficient inference on resource-constrained devices

    2026 · Information Processing & Management · Zhang, Zhipeng, Ilvovsky, Dmitry

    2026

28. Evaluating the Effectiveness of Lightweight Cryptographic Algorithms for Resource-Constrained IoT Devices in Smart Home Environments

    2026 · Pindal, Sourav, Singh, Sandeep, Shakari, Soman et al.

    2026

29. SPIDER: Lightweight Speaker Identification on Resource-Constrained Embedded Devices

    2026 · Gallacher, Markus, Boano, Carlo Alberto, Pillai, Arun Sankar Muttathu Sivasankara et al.

    2026

30. HCInfer: An Efficient Inference System via Error Compensation for Resource-Constrained Devices

    2026 · ArXiv.org · Xu, Shen, Zhuge, Xiangwen, Xu, Zhe et al.

    2026