AffectStream: Kafka-based Real-time Affect Monitoring System using Wearable Sensors

Real-time affect monitoring is essential for personalized and adaptive applications in fields like education, healthcare, and customer service. However, existing systems often struggle with scalability and low-latency requirements for processing high-frequency sensor data. To address these challenges, we propose AffectStream, a Kafka-based real-time affect monitoring system that processes wearable sensor data through a cloud-based pub/sub architecture to the applications. AffectStream ensures scalability, fault tolerance, and personalized emotional state analysis. Its robust performance is demonstrated through trace-based evaluations using the WESAD dataset. This open-source framework advances real-time emotion recognition, paving the way for large-scale affective computing applications.

Code Structure Overview

📦 AffectStream/
 ┣ 📂 analysis/
 ┣ 📂 components/
 ┣ 📂 infrastructure/
 ┣ 📜 .gitignore
 ┣ 📜 LICENSE
 ┗ 📜 README.md

1. analysis/

This folder contains sql script, performance evaluations, and experiment results.

• Contents
  • SQL script for querying data and extracting insights (.sql)
  • Jupyter notebook for result visualization (.ipynb)

2. components/

This folder contains the core application modules, including Kafka consumers, producers, and simulators.

• Contents
  • consumer/: Kafka consumers responsible for processing messages from topics.
  • kafka_management/: Handles Kafka configurations, including topic creation, monitoring, and security.
  • producer/: Kafka producers that publish messages to specified topics.
  • simulator/: Simulates real-time data streaming for testing and benchmarking.

3. infrastructure/

This folder manages the deployment of components from the components/ folder and infrastructure configurations, including Kubernetes and Docker.

• Conents
  • kubernetes/: Contains Kubernetes manifests (.yaml files) for deploying and managing services, deployments, and networking.
  • terraform/: Infrastructure-as-Code (IaC) configurations for provisioning cloud resources such as databases, compute instances, and networking using Terraform.