Build the fleet analytics you actually need
IoT Query turns telematics data into a first-class analytical data source, compatible with all major BI tools and Python/R ecosystems. Explorer for IoT Query + SQL Recipe Book + open-source dashboard builder drastically shorten time-to-value.
SQL-first, tool-agnostic analytics
IoT Query provides a PostgreSQL-compatible endpoint — connect from any SQL-capable tool. API-less means no rate limits and complete schema visibility.
Use standard Postgres drivers and SQL syntax. Connect from anywhere — Power BI, Tableau, Python, R, or even Excel.
Query as much data as you need, whenever you need it. No throttling, no pagination, no waiting for exports.
Browse all tables, columns, and relationships. Understand your data structure at a glance with full metadata access.
Get credentials → add Postgres connection in Power BI/Tableau/Superset/Metabase → start building dashboards.
Explorer for IoT Query – instant visibility
Explorer for IoT Query is a ready-to-use Streamlit app providing real-time dashboards, historical reports, and custom SQL analysis. Open-sourced and fully extensible.
Real-Time Dashboards
Live fleet & sensor status monitoring
- •Current vehicle locations and status
- •Active alerts and events
- •Connection health monitoring
Historical Reports
Sensor trends, utilization, and workforce analytics
- •Sensor measurement trends over time
- •Object activity and utilization reports
- •Shifts and workforce productivity analysis
Custom Analysis & SQL
Full SQL query interface with interactive visualizations
- •Write custom SQL queries against any table
- •Interactive chart builder for query results
- •Schema browser for exploring data structure
Connect your favorite BI tools in minutes
IoT Query works with any SQL-capable tool. Choose what fits your team best — from enterprise reporting platforms to lightweight open-source dashboards.
Power BI
For corporate reporting & governance. Enterprise-grade dashboards with Active Directory integration.
Superset / Metabase
For embedded or lightweight dashboards. Open-source, easy to deploy, great for internal tools.
Python + Streamlit
For custom domain apps and open-sourced Explorer-like projects. Maximum flexibility and control.
Tableau / Looker
For advanced visualizations and enterprise analytics. Connect via standard Postgres driver.
Access raw sensor data for custom feature extraction with SQL & Python
Use cleansed, enriched data with derived KPIs for ML training
Integrate trained models back into Navixy platform via IoT Logic or APIs
From dashboards to ML & AI
IoT Query's layered architecture enables data science teams to build predictive models, optimize operations, and create AI-driven features using full-fidelity telematics data.
Build models to forecast component failures weeks in advance based on sensor patterns and historical repair data.
Train models on historical trip data, traffic patterns, and weather to optimize routes and predict accurate ETAs.
Calculate driver risk scores and eco-driving metrics for insurance underwriting and tender evaluations.
Recipes & examples
Real-world SQL queries and analytical patterns from the Navixy SQL Recipe Book. Learn by example and adapt for your use cases.
Vehicles in geofences during off-hours
Security and evidence — detect unauthorized asset usage by identifying vehicles in restricted zones outside working hours.
Fuel anomaly detection
Identify sudden fuel drops vs expected consumption patterns to catch potential theft or sensor malfunctions.
Eco-driving score with custom thresholds
Calculate driver performance scores based on your own KPIs — speeding, harsh braking, idling, and acceleration patterns.
Proactive TSP support health dashboard
Monitor device health, SIM connectivity, and support ticket trends to identify issues before customers complain.
Future analytics capabilities
IoT Query is continuously evolving. Here's what's coming next to make your analytics even more powerful.
PostGIS-Compatible Geospatial Functions
Perform geofence and route analysis directly in SQL. Check if coordinates fall inside zones or calculate distances between points.
Time-Window Helpers
Filter by shift schedules, working hours, or custom recurring time periods inspired by iCalendar logic — no complex SQL required.
Pre-Built Gold Data Marts
Ready-made analytical datasets for eco-driving, maintenance, logistics, and support — plug and play for common use cases.
Book a technical walkthrough for your data team
Our analytics experts will walk you through IoT Query capabilities, show how to connect your tools, and discuss your specific use cases and KPIs.