Author

T. Sardar

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Open access Sep 2026

Multimodal deep learning framework for LoRaWAN based crop health monitoring

This study proposes AgriPredict–LoRaWAN Network (APLNet), an Internet of Things (IoT)-based agricultural monitoring and disease classification framework designed for cucumber farming that supports timely decision-making, improves productivity, reduces crop losses, and promotes sustainable cucumber cultivation.

P. Theerthagiri, A. Ruby, J. C. Chandran et al. · Scientific Reports · 0 citations

Open access Aug 2026

Integrated design of an efficient multi spectral imaging and federated learning framework for precision crop disease diagnosis in low-resource farming communities

This research introduced a comprehensive multi-spectral imaging and machine learning framework that can easily revolutionize the disease diagnosis and management inside the low-resource farming communities while supporting scalability with actionable insights to empower farmers to mitigate crop losses and augment food...

J. Sastry, Pannangi Naresh, A. Ayesha et al. · Scientific Reports · 0 citations

#federated learning Open access Aug 2026

AI‐Enabled 6G Space‐Air‐Ground–Integrated Networks for Ultra‐Reliable Low Latency Internet of Medical Things Healthcare

An AI‐assisted resource scheduling and cooperative learning model in a space–air–ground combined network (SAGIN) to possess ultra‐reliable low‐latency Internet of Medical Things applications and a multi agent—deep deterministic policy gradient (MA‐DDPG) agent that allocates resources in a distributed manner and a hiera...

T. Sardar, Gousia Thahniyath, Ahlam I. Almusharraf et al. · Transactions on Emerging Tel... · 0 citations