Artificial Intelligence of Things (AIoT)
Detailed Schedule
Session 1
09:30 – 10:00
Welcome by Workshop Chairs
10:00 – 10:30
Unlocking AIoT Efficiency in the Computing Continuum - the PANDORA Framework
Dr. Asterios Stroumpoulis
10:30 – 11:00
TBD
Dr. Pandarasamy Arjunan (Assistant Professor, IISc Bengaluru)
11:00 – 11:30
Tea/Coffee
Session 2: Resilient & Secure Edge Intelligence for AIoT Systems
11:30 – 11:50
Tiny Yet Mighty: Quantized Deep Learning for Edge Plant Disease Detection
Saud Masaud Alam; Aniruddh Jain; Nikhil Tiwari Patel Mahekkumar Ghelabhai; Sourajit Behera
11:50 – 12:10
Adaptive Task Scheduling in Edge-Fog-Cloud with Network Failure Resilience
Sahil Padole; Ajay Kattepur
12:10 – 12:30
Low-Cost IoT-Based Downtime Detection For UPS and Behaviour Analysis
Sannidhya Gupta; Prakash Nayak; Sachin Chaudhari
12:30 – 12:50
DP-EMAR: A Differentially Private Framework for Autonomous Model Weight Repair in Federated IoT Systems
Chethana Prasad Kabgere; Shylaja S S
12:50 – 14:00
Lunch Break
Session 3: AI-Enhanced IoT Sensing and Edge Intelligence
14:00 – 14:20
Edge Intelligence for Speech: Evaluating Model Performance, Feature Extraction and Signal Fidelity on Commodity Hardware
Shubham; Loukik Darsi; Avaneesh Pothuri; Manik Gupta; RN Ponnalagu
14:20 – 14:40
IoT-Assisted Estimation of Vehicular Traffic Status over Wide-Area
Anwesha Patel; Sudipta Saha
14:40 – 15:00
Real-Time Big Data Analytics for Predictive Healthcare Monitoring using IoT and Cloud Integration
Chitiz Tayal
15:00 – 15:20
Human Activity Recognition Using 5G RF Sensing and Interpretable Tsetlin Machines
Charitha Gadari; Sreenivasa Reddy Yeduri; Ole-Christoffer Granmo; Linga Reddy Cenkeramaddi, Sr
15:20 – 15:40
Green AI Orchestration Bridging Trustworthy AI and Edge AI through tinyML for Frugal Intelligence
Joao Costa; Marco Zennaro; Ioana Ntinou; John S Shawe-Taylor
15:40 – 16:00
TinyVLM: A Distilled and Quantized Vision-Language Model for Efficient Food Image-Text Retrieval in TinyML Settings
Podakanti Satyajith Chary; Pithani Teja Venkata Ramana Kumar; Nagarajan Ganapathy
16:00 – 16:30
Tea Break (along with poster session)
Session 4: Advanced AIoT Decision Systems: Federated, Secure, and Autonomous Intelligence
16:30 – 16:50
FedVAD: A Privacy-Preserving Federated Voice Anomaly Detection Framework for Child Safety
Yagyansh Gupta; Shyam Navinkumar Modi; Neha Agrawal
16:50 – 17:10
COSTAR: Cloud-Observed Safety and Trust-Aware Agentic Reasoning for Enterprise Workflows
Sowjanya Pandruju
17:10 – 17:30
Multimodal RL for Game Recommendation using Dual-Discriminator PPO Framework
Ayush Deshmukh; Siddharth Kelkar; Anand Kumar M
17:30 – 17:50
Fast Domain Adaption and Model Compression for IoT devices using Meta-Learning and Federated Knowledge Distillation
Nelson Sharma; Nirmit Chaurasia; Lavanya Bhadani; Rajiv Misra; Supratik Mukhopadhyay
17:50 – 18:15
Closing & Best Paper Award announcement
Call for Papers
Camera Ready Guidelines
Accepted Papers
-
SecureFed-AIoT: A Trust-Weighted Federated Learning Framework for Secure and Resilient Edge Intelligence
-
Adaptive Task Scheduling in Edge-Fog-Cloud with Network Failure Resilience
-
DP-EMAR: A Differentially Private Framework for Autonomous Model Weight Repair in Federated IoT Systems
-
Low-Cost IoT-Based Downtime Detection For UPS and Behaviour Analysis
-
Green AI Orchestration Bridging Trustworthy AI and Edge AI through tinyML for Frugal Intelligence
-
Multimodal RL for Game Recommendation using Dual-Discriminator PPO Framework
-
TinyVLM: A Distilled and Quantized Vision-Language Model for Efficient Food Image-Text Retrieval in TinyML Settings
-
Edge Intelligence for Speech: Evaluating Model Performance, Feature Extraction and Signal Fidelity on Commodity Hardware
-
FedVAD: A Privacy-Preserving Federated Voice Anomaly Detection Framework for Child Safety
-
IoT-Assisted Estimation of Vehicular Traffic Status over Wide-Area
-
Human Activity Recognition Using 5G RF Sensing and Interpretable Tsetlin Machines
-
COSTAR: Cloud-Observed Safety and Trust-Aware Agentic Reasoning for Enterprise Workflows
-
Real-Time Big Data Analytics for Predictive Healthcare Monitoring using IoT and Cloud Integration
-
Fast Domain Adaption and Model Compression for IoT devices using Meta-Learning and Federated Knowledge Distillation
-
Tiny Yet Mighty: Quantized Deep Learning for Edge Plant Disease Detection
Important Dates
| Paper Submission deadline: |
| Notification of Acceptance: |
| Camera-ready Submission: |
| Workshop Date: 10th January 2026 |
Workshop Overview
Topics of Interest:
AI for IoT focuses on enabling machine learning and intelligent computing on resource-constrained, secure, and connected devices. We invite submissions of innovative technologies, frameworks, and applications that advance the IoT ecosystem. Topics include, but are not limited to:
- On-device machine learning algorithms
- TinyML and embedded AI for resource-constrained devices
- Real-time computer vision and speech processing
- Federated learning in IoT environments
- AI model compression, quantization, and pruning techniques
- Learning-enabled IoT applications
- Edge AI
- AI for IoT security and privacy
- Energy Efficient AI for IoT systems
- Distributed inference and learning
- Optimized blockchain for IoT
- AIoT solution risk evaluation and control
- Systems and software engineering for IoT
- AI-driven IoT protocols design
- IoT system architecture and enabling technologies
- Demonstration of AI-enabled IoT applications
Submission Guidelines
- The AIOT Workshop invites original research work not previously published or under review elsewhere.
- Submissions (including title, authors, abstract, figures, tables, and references) must not exceed 6 pages.
- Double-blind review: Authors’ names and affiliations must not appear in the submission.
- Submissions must follow the IEEE formatting guidelines; non-compliant papers will not be reviewed.
- All papers must be in PDF format and submitted via the AIOT Workshop submission site on EDAS: https://edas.info/N34103
- Accepted workshop papers will appear in the conference proceedings and will be submitted to IEEE Xplore and other indexing databases.
Papers can be submitted through EDAS: https://edas.info/N34103
For any queries, please contact the workshop chairs at comsnets.workshop@gmail.com
Technical Program Committee
- Maria Pateraki (National Technical University of Athens)
- Konstantinos Tserpes (National Technical University of Athens)
- Dušan Jakovetić (University of Novi Sad)
- Sotiris Ioannidis (Technical University of Crete)
- Patrizio Dazzi (University of Pisa)
- Katerina Tzompanaki (Cergy Paris University)
- Houssam Hajj Hassan (Télécom SudParis)
- Arne Bröring (Siemens)
- Miloš Savić (University of Novi Sad)
- Vladimir Kurbalija (University of Novi Sad)
- Patrizio Frosini (University of Pisa)
- Ourania Manta (Cyberalytics Limited)
- Karl Waedt (Framatome)
- Mohammad Hamad (Technical University of Munich)
- Branislav Vrban (Slovak University of Technology)
- Konstantina Agoraki (University of Piraeus)
Artificial Intelligence of Things (AIoT) Workshop Co-Chairs
Punit Rathore
Indian Institute of Science
Bengaluru, India
Asterios Stroumpoulis
National Technical University of Athens
Greece
Ajay Kattepur
Ericsson Research
Bangalore, India