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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
A Lora-Based and Maintenance-Free Cattle Monitoring Syste...
Lukas Schulthess, Fabrice Longchamp, Christian Vogt, Michele Mag · 2024-06-10 · via eess.SP updates on arXiv.org

The advent of the Internet of Things (IoT) is boosting the proliferation of sensors and smart devices in industry and daily life. Continuous monitoring IoT systems are also finding applications in agriculture, particularly in the realm of smart farming. The adoption of wearable sensors to record the activity of livestock has garnered increasing interest. Such a device enables farmers to locate, monitor, and constantly assess the health status of their cattle more efficiently and effectively, even in challenging terrain and remote locations. This work presents a maintenance-free and robust smart sensing system that is capable of tracking cattle in remote locations and collecting activity parameters, such as the individual's grazing- and resting time. To support the paradigm of smart farming, the cattle tracker is capable of monitoring the cow's activity by analyzing data from an accelerometer, magnetometer, temperature sensor, and Global Navigation Satellite System (GNSS) module, providing them over Long Range Wide Area Network (LoRaWAN) to a backend server. By consuming 511.9 J per day with all subsystems enabled and a data transmission every 15 minutes, the custom-designed sensor node achieves a battery lifetime of 4 months. When exploiting the integrated solar energy harvesting subsystem, this can be even increased by 40% to up to 6 months. The final sensing system's robust operation is proven in a trial run with two cows on a pasture for over three days. Evaluations of the experimental results clearly show behavior patterns, which confirms the practicability of the proposed solution.