IEEE

An IoT-Based Real-Time Elevator Health Monitoring System Using LSTM Autoencoder

Abstract: Elevators play an essential role for safe and efficient vertical transportation in modern buildings. However, traditional maintenance strategies based on scheduled inspections often fail to ...
GitHub

striim-labs/lstm-autoencoder-spark-kafka

Real-time anomaly detection on NYC taxi demand data using an LSTM Encoder-Decoder model, Kafka streaming, Spark Structured Streaming, and a Dash visualization dashboard. Based on Malhotra et al. (2016 ...
Scientific Research Publishing

A Hybrid CNN-LSTM Variational Autoencoder for Treatment Response Prediction in Synthetic Psychiatric Data ()

Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of conventional ...
Scientific Research Publishing

Al-Qatf, M., Lasheng, Y., Al-Habib, M. and Al-Sabahi, K. (2018) Deep Learning Approach Combining Sparse Autoencoder with SVM for Network Intrusion Detection. IEEE Access, 6 ...

ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...
GitHub

ranasaurabh191/Predictive-Maintenance-PdM-Pipeline

textpdmp_project/ │ ├── data/ │ ├── raw/ # Raw synthetic sensor data (e.g., synthetic_sensor_data.csv) │ └── processed/ # Processed data (e.g ...
IEEE

Attention-Based LSTM Autoencoder for Noise-Resilient Semantic Communication for IoT Devices in 6G Networks

Abstract: Semantic communication (SC) has emerged as a key enabler for 6G networks to overcome the Shannon limit. SC aims to transmit meaning rather than raw data. In this context, many researchers ...