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eess.SP updates on arXiv.org

ECG-biometrics-bench: A Unified Framework for Reproducible Benchmarking of ECG Biometrics Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning Towards Improving Speaker Distance Estimation through Generative Impulse Response Augmentation Federated Learning with Hypergradient-based Online Update of Aggregation Weights Soft Graph Diffusion Transformer for MIMO Detection SPLICE: Latent Diffusion over JEPA Embeddings for Conformal Time-Series Inpainting Sequential Inference for Gaussian Processes: A Signal Processing Perspective Statistical Channel Fingerprint Construction for Massive MIMO: A Unified Tensor Learning Framework Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation Adaptive Transform Coding for Semantic Compression EdgeSpike: Spiking Neural Networks for Low-Power Autonomous Sensing in Edge IoT Architectures Sparse Graph Learning from Sparse Data via Fiedler Number Maximization A Deep Learning Model for Battery State Prediction towards Intelligent Energy Management Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals EVT-Based Generative AI for Tail-Aware Channel Estimation Monitoring exposure-length variations in submarine power cables using distributed fiber-optic sensing BandRouteNet: An Adaptive Band Routing Neural Network for EEG Artifact Removal Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring Speech Enhancement Based on Drifting Models Robust and Clinically Reliable EEG Biomarkers: A Cross Population Framework for Generalizable Parkinson's Disease Detection An AI-Based Supervisory Measurement Integrity Validation Layer for Cyber-Resilient AC/DC Protection in Inverter-Based Microgrids Explainable AI in Speaker Recognition -- Making Latent Representations Understandable Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals An Algorithm for On-Sensor Agnostic Detection of Changes in Human Activity for Ultra-Low-Power Applications
Sustainable and Precision Agriculture with the Internet o...
Adil Z. Babar, Ozgur B. Akan · 2024-04-09 · via eess.SP updates on arXiv.org

Agriculture faces critical challenges from population growth, resource scarcity, and climate change, driving a shift toward advanced, technology-integrated farming. Mechanization has transformed agriculture, enhancing sustainability and crop productivity. Now, technologies like artificial intelligence (AI), robotics, biotechnology, blockchain, and the Internet of Things (IoT) are advancing precision agriculture. The concept of the Internet of Everything (IoE) has gained traction due to its holistic approach to integrating various IoT specializations, called IoXs with X referring to a specific domain. This paper explores the transformative role of IoE in agriculture, expanding beyond traditional IoT applications to integrate niche subdomains like molecular communication (MC), the Internet of Nano Things (IoNT), the Internet of Bio-Nano Things (IoBNT), designer phages, and the Internet of Fungus (IoF). Our study provides a detailed review of how these IoE subdomains, in conjunction with 6G, blockchain, and machine learning (ML), can enhance precision farming in areas like crop monitoring, resource management, and disease control. Unlike prior IoT centric reviews, this work uniquely focuses on IoEs potential to advance agriculture at molecular and biological scales, achieving more precise resource utilization and resilience. Key contributions include an exploration of these technologies applicability, associated challenges, and recommendations for future research directions within precision agriculture.