TeslaMate Automation Dashboard

Active

Digital Life Experiments

A Tesla vehicle data dashboard built on TeslaMate, Grafana, InfluxDB, and PostgreSQL, with trip records, charging analysis, energy metrics, alerts, and weekly reports.

English TeslaMate Dashboard project cover showing vehicle telemetry, charging curves, and digital-life automation
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Project Profile

Phase
Digital Life Experiment
Visibility
Project Record
Next Step
Keep reviewing vehicle data, charging cost, energy trends, Grafana dashboards, and automation reminders.
Project Relation
A personal digital-life experiment that turns real device data into an observable and reviewable data system.
Boundary
It is personal data engineering practice, not an AI flagship project, and private trip data is not exposed.
Tech Stack
  • Docker
  • TeslaMate
  • InfluxDB
  • Grafana
  • PostgreSQL
digital-lifeautomationdata-visualizationDocker

Project Background

TeslaMate is an open-source data logger for Tesla vehicles. The default Grafana dashboards are useful, but I wanted a more personal view of trips, charging behavior, energy usage, and automation alerts.

This project customizes the TeslaMate stack and adds dashboards and notification rules that match my daily driving and charging workflow.

Architecture

The system uses TeslaMate to collect vehicle data, PostgreSQL for structured records, InfluxDB for time-series metrics, and Grafana for visualization. Everything runs through Docker Compose on a home NAS.

The data flow is intentionally simple:

  • Tesla API provides vehicle state and trip data
  • TeslaMate stores trip and charging records
  • PostgreSQL keeps structured history
  • InfluxDB stores high-frequency time-series data
  • Grafana renders dashboards for review and alerts

Custom Dashboards

The dashboard layer focuses on questions I actually check:

  • Weekly mileage, driving time, and energy consumption
  • Charging speed and efficiency trends
  • Location-based trip review
  • Energy usage by route and driving context
  • Long-term battery and charging habit observation

Automation

The automation layer adds practical notifications, including charge completion reminders, low-battery alerts, and weekly summaries. The goal is to make vehicle data useful without having to manually open Grafana every day.

Current Value

This project is a digital-life experiment and a lightweight example of personal data engineering: collect data from a real device, normalize it, visualize it, and turn it into timely operational feedback. Public notes keep the architecture abstract and do not expose real hosts, accounts, alert tokens, or internal configuration.

Relationship with Other Projects

TeslaMate does not compete with the AI engineering projects at the same weight. It belongs to digital-life experiments: using engineering methods to observe real device data and turn trips, charging, energy usage, and reminders into a reviewable small system.

Project Asset

Asset Connections

How this project connects to topics, reading paths, series, and future writing.

Related Topics

Long-term Records & Digital LifeBackend Engineering & Microservices

Reading Paths

Related Series

  • All SeriesDigital-life experiments are project records for now

Related Entries

  • AnalyticsSite and data-observation method entry

Project Timeline

Next Content Plan

  • Add data source, observation metrics, automatic records, weekly reports, and periodic review method.
  • Keep the digital-life experiment boundary explicit without exposing private trips or internal config.

Project FAQ

Will the TeslaMate project expose real trip data?
No. The public page only explains architecture and review method, not real locations, accounts, tokens, or internal config.