Request Demo

Partners & Integrations for Smart City IoT Aggregation

Our extensive integration ecosystem enables seamless data flow between sensors, systems, and applications, creating a unified smart city infrastructure.

Integration Ecosystem Overview

The NeuraAtlas platform is designed with interoperability as a core principle, enabling seamless connections with existing infrastructure, third-party systems, and specialized analytics tools. Our integration framework serves multiple strategic objectives:

Data Ingestion

Connect diverse sensor networks regardless of protocol or manufacturer, enabling unified data collection from heterogeneous sources.

Protocol Bridges

Translate between communication standards to ensure compatibility across legacy and modern systems without requiring hardware replacement.

Analytics Connectors

Export processed data to specialized visualization and analytics platforms, enhancing insights through purpose-built tools.

Our integration approach prioritizes standardization, security, and performance, ensuring that data flows reliably while maintaining integrity and privacy compliance.

Protocol Bridges & Brokers

Connect any sensor network to our platform through our comprehensive protocol translation layer, supporting both modern and legacy communication standards.

Visualization of protocol bridges connecting different IoT communication standards with data streams transforming between formats

Supported Protocols

IoT-Specific

  • MQTT (v3.1.1, v5.0)
  • CoAP (RFC 7252)
  • LwM2M
  • AMQP
  • DDS

Web Standards

  • HTTP/HTTPS (REST)
  • WebSockets
  • Server-Sent Events
  • GraphQL
  • gRPC

Protocol Bridge Features

  • QoS Management: Configurable Quality of Service levels with automatic retry and persistence mechanisms
  • Protocol Translation: Seamless conversion between protocols while preserving message semantics and metadata
  • Authentication Bridge: Unified authentication framework across different protocol security models
  • Message Transformation: Content adaptation, filtering, and enrichment during protocol conversion
  • Performance Optimization: Protocol-specific tuning for bandwidth conservation and latency reduction

Security Considerations

All protocol bridges implement comprehensive security measures, including:

  • TLS/DTLS encryption for all communications
  • Certificate-based authentication
  • Message signature verification
  • Rate limiting and anomaly detection
  • Protocol-specific vulnerability mitigation

Protocol Bridge Implementation Example

The following example demonstrates how to connect a sensor network using MQTT to our platform:

# MQTT to Platform Bridge Configuration Example

# Broker Connection Settings
broker:
  host: mqtt.neuraatlas.com
  port: 8883
  client_id: "city-district-bridge-${ZONE_ID}"
  use_tls: true
  cert_file: "/path/to/client.crt"
  key_file: "/path/to/client.key"
  ca_file: "/path/to/ca.crt"

# Topic Mapping
topic_mapping:
  - source: "sensors/+/temperature"
    destination: "data/environmental/temperature"
    transform: "payload.temp = payload.value * 1.8 + 32"
  
  - source: "sensors/+/humidity"
    destination: "data/environmental/humidity"
    transform: null

# QoS Settings
qos:
  default_level: 1
  persistence: true
  retry_interval: 30
  max_retries: 5

# Authentication
auth:
  method: "certificate"
  username_template: "device-${DEVICE_ID}"

Time-Series DB Integrations

Our platform connects with specialized time-series databases to provide optimized storage and retrieval for IoT sensor data at scale.

Database Integration Features

  • Optimized Write Patterns: Specialized connectors that understand time-series write characteristics, including batch inserts and compaction
  • Retention Management: Automated data lifecycle policies synchronized across integrated databases
  • Schema Adaptation: Dynamic schema mapping between different database models
  • Query Translation: Conversion between query languages while preserving time-series semantics
  • Replication Support: Cross-database replication for redundancy and geographic distribution

Performance Optimizations

Our database integrations implement specialized techniques for time-series data management:

  • Compression Algorithms: Delta encoding, run-length encoding, and Gorilla compression reduce storage requirements by up to 95%
  • Partitioning Strategies: Time-based partitioning with automatic hot/warm/cold data management
  • Query Acceleration: Materialized views and pre-aggregation for common time-series operations
  • Adaptive Caching: Pattern-aware caching that recognizes temporal access patterns
Visualization of time-series database structure showing data points organized in temporal sequences with compression algorithms condensing older data

Supported Database Types

Specialized Time-Series

  • InfluxDB
  • TimescaleDB
  • QuestDB
  • OpenTSDB
  • Prometheus

General Purpose with TS Extensions

  • PostgreSQL (with TimescaleDB)
  • MongoDB (with time-series collections)
  • Cassandra (with time-series model)
  • ClickHouse
  • Amazon Timestream

Time-Series Integration Example

The following example demonstrates a typical query integration that translates between our platform's query language and a specific time-series database:

// Time-Series Query Translation Example

// Original Platform Query
const platformQuery = {
  metric: "temperature",
  tags: { location: "district-5", sensor_type: "outdoor" },
  aggregation: "avg",
  interval: "1h",
  timeRange: {
    start: "2025-01-01T00:00:00Z",
    end: "2025-01-07T23:59:59Z"
  }
};

// Translated to InfluxDB Query
const influxQuery = `
SELECT mean("value") AS "avg_temperature"
FROM "sensors"."temperature"
WHERE "location" = 'district-5' AND "sensor_type" = 'outdoor'
  AND time >= '2025-01-01T00:00:00Z' AND time <= '2025-01-07T23:59:59Z'
GROUP BY time(1h)
`;

// Translated to TimescaleDB (PostgreSQL) Query
const timescaleQuery = `
SELECT 
  time_bucket('1 hour', time) AS bucket,
  AVG(value) AS avg_temperature
FROM temperature_readings
WHERE location = 'district-5' AND sensor_type = 'outdoor'
  AND time >= '2025-01-01T00:00:00Z' AND time <= '2025-01-07T23:59:59Z'
GROUP BY bucket
ORDER BY bucket
`;

Dashboard & BI Integrations

Connect our platform's real-time data streams to specialized visualization and business intelligence tools for enhanced insights and reporting.

Real-time Dashboards

Our WebSocket and Server-Sent Events connectors enable live data visualization in popular dashboard platforms with sub-second latency.

  • Bi-directional data flow with control capabilities
  • Optimized for high-frequency updates
  • Automatic reconnection and data backfilling

Export Formats

Our platform supports a wide range of export formats for integration with analytics and reporting tools.

  • Structured: JSON, CSV, Parquet, Avro
  • Time-series optimized: Arrow, PromQL
  • GIS formats: GeoJSON, Shapefile

Integration Methods

Multiple integration approaches to suit different technical requirements and security constraints.

  • Direct API access with OAuth 2.0
  • Embedded iframe with signed URLs
  • Data push via webhooks and connectors

Supported Visualization Platforms

Real-time Dashboards

  • Grafana
  • Kibana
  • Tableau
  • Power BI
  • Superset

GIS & Mapping

  • QGIS
  • ArcGIS
  • Mapbox
  • CARTO
  • Kepler.gl

Business Intelligence

  • Looker
  • Domo
  • Sisense
  • QlikView
  • Metabase

Specialized Analytics

  • Jupyter Notebooks
  • RStudio
  • KNIME
  • Alteryx
  • DataRobot

Edge & Gateway Partners

Our platform integrates with edge computing devices and gateways to enable distributed intelligence and reduce latency in smart city deployments.

Close-up of edge computing hardware deployed in a smart city environment with visible cooling systems and connectivity arrays

Edge Integration Capabilities

  • Containerized Deployment: Pre-configured Docker containers and Kubernetes manifests for rapid edge deployment
  • Resource Optimization: Adaptive resource allocation based on edge device capabilities
  • Offline Operation: Local data storage and processing during connectivity interruptions
  • Mesh Networking: Device-to-device communication for resilient data transmission
  • OTA Updates: Secure over-the-air updates with rollback capabilities

Edge Device Categories

Industrial Gateways

  • Ruggedized outdoor enclosures
  • Extended temperature ranges
  • Multiple connectivity options
  • DIN rail mounting options
  • Industrial protocol support

Smart City Nodes

  • Pole/streetlight mounting
  • Solar/battery power options
  • Integrated sensors
  • Mesh network capabilities
  • Public Wi-Fi options

Edge Processing Functions

  • Data Filtering: Local rules engine for data reduction and noise filtering
  • Aggregation: Statistical aggregation to reduce transmission volume
  • Event Detection: Pattern recognition for immediate local response
  • ML Inference: Optimized models for edge-based prediction
  • Data Encryption: Local encryption for secure transmission

Edge Deployment Example

The following configuration demonstrates a typical edge node deployment in a smart city environment:

// Edge Node Configuration Example

{
  "node_id": "edge-district5-node12",
  "location": {
    "lat": 54.6872,
    "lng": 25.2797,
    "zone": "district-5",
    "description": "Intersection of Main St and Oak Ave"
  },
  "hardware": {
    "model": "NeuraEdge-3000",
    "cpu": "4 cores @ 1.5GHz",
    "ram": "4GB",
    "storage": "128GB SSD",
    "power": "PoE+ / Solar backup"
  },
  "connectivity": {
    "primary": {
      "type": "fiber",
      "bandwidth": "1Gbps",
      "provider": "CityNet"
    },
    "backup": {
      "type": "lte",
      "bandwidth": "50Mbps",
      "provider": "MobileLink"
    },
    "mesh": {
      "enabled": true,
      "protocol": "802.11s",
      "peers": ["edge-district5-node11", "edge-district5-node13"]
    }
  },
  "processing": {
    "filters": [
      {
        "sensor_type": "traffic",
        "condition": "value.count < 2",
        "action": "drop"
      },
      {
        "sensor_type": "environmental",
        "condition": "abs(value - last_value) < threshold",
        "action": "drop",
        "parameters": {
          "threshold": {
            "temperature": 0.5,
            "humidity": 2.0,
            "air_quality": 5.0
          }
        }
      }
    ],
    "aggregations": [
      {
        "sensor_type": "traffic",
        "window": "5m",
        "functions": ["avg", "max", "count"],
        "group_by": ["direction", "vehicle_type"]
      }
    ],
    "events": [
      {
        "name": "high_congestion",
        "condition": "traffic.count > 100 && traffic.speed < 10",
        "actions": [
          {
            "type": "alert",
            "priority": "high",
            "recipients": ["traffic_control", "emergency_services"]
          },
          {
            "type": "actuator",
            "target": "traffic_signals",
            "command": "congestion_mode"
          }
        ]
      }
    ]
  }
}

Alerts & Notification Systems

Our platform integrates with diverse notification systems to ensure critical alerts reach the right stakeholders through their preferred channels.

Alert Channels

Multiple notification pathways ensure alerts reach stakeholders through their preferred communication methods.

  • Email with priority flagging
  • SMS and voice calls for critical alerts
  • Mobile push notifications
  • Integration with incident management platforms

Alert Rules Engine

Sophisticated rules processing for accurate alert generation and intelligent routing.

  • Multi-condition triggers with boolean logic
  • Temporal patterns (duration, frequency, sequence)
  • Geo-fencing and location-based rules
  • Machine learning anomaly detection

Stakeholder Management

Targeted notification delivery based on roles, responsibilities, and escalation paths.

  • Role-based alert routing
  • Time-based escalation paths
  • On-call rotation integration
  • Acknowledgment tracking and SLA monitoring

Alert Integration Partners

Incident Management

  • PagerDuty
  • OpsGenie
  • VictorOps
  • xMatters
  • ServiceNow

Communication Platforms

  • Twilio
  • Vonage
  • MessageBird
  • SendGrid
  • Mailgun

Team Collaboration

  • Slack
  • Microsoft Teams
  • Discord
  • Mattermost
  • Telegram

Public Safety Systems

  • Emergency Alert System
  • CAD Integration
  • Public Warning Systems
  • First Responder Platforms
  • Traffic Management Systems

API & Webhooks Overview

Our comprehensive API ecosystem enables custom integrations and extensions, allowing you to build specialized applications on top of our platform.

API Architecture

Our API is designed following REST principles with consistent patterns across endpoints. The architecture includes:

  • Resource-oriented Design: Clear URL structure representing resources and relationships
  • Consistent Methods: Standard HTTP verbs (GET, POST, PUT, DELETE) with predictable behavior
  • Comprehensive Documentation: OpenAPI/Swagger specifications with interactive exploration
  • Versioning Strategy: URL-based versioning for backward compatibility
  • Rate Limiting: Transparent limits with clear headers and graceful throttling

Authentication & Authorization

  • OAuth 2.0: Industry-standard authorization framework
  • API Keys: Simple authentication for machine-to-machine integration
  • JWT Tokens: Stateless authentication with fine-grained claims
  • Scoped Permissions: Granular access control to specific resources and actions
  • IP Allowlisting: Additional security layer for critical endpoints

Webhooks System

Our webhook infrastructure enables real-time push notifications for platform events:

  • Event Types: Comprehensive catalog of triggerable events
  • Payload Customization: Configure exactly what data is included in notifications
  • Delivery Guarantees: Retry mechanism with exponential backoff
  • Security: HMAC signature verification for payload validation
  • Monitoring: Detailed delivery logs and performance metrics

API Categories

Data Management

  • Sensor registration
  • Data ingestion
  • Query and retrieval
  • Metadata management

Analytics

  • Aggregation functions
  • Statistical analysis
  • Anomaly detection
  • Forecasting

Administration

  • User management
  • Permission control
  • Audit logging
  • System configuration

Integration

  • Webhook management
  • Export configuration
  • Protocol settings
  • Edge deployment

API Examples

The following examples demonstrate typical API interactions with our platform:

Data Retrieval Example

// Request
GET /api/v1/data/sensors/temperature?location=district-5&start=2025-01-01T00:00:00Z&end=2025-01-02T00:00:00Z&interval=1h
Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...
Accept: application/json

// Response
{
  "status": "success",
  "data": {
    "sensor_type": "temperature",
    "location": "district-5",
    "unit": "celsius",
    "interval": "1h",
    "readings": [
      {
        "timestamp": "2025-01-01T00:00:00Z",
        "value": 21.5,
        "min": 20.8,
        "max": 22.3,
        "count": 12
      },
      {
        "timestamp": "2025-01-01T01:00:00Z",
        "value": 20.9,
        "min": 20.1,
        "max": 21.7,
        "count": 12
      },
      // Additional data points...
    ]
  },
  "meta": {
    "total_points": 24,
    "aggregation": "avg"
  }
}

Webhook Configuration Example

// Request
POST /api/v1/webhooks
Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...
Content-Type: application/json

{
  "name": "Traffic Alert Notification",
  "target_url": "https://traffic.citymanagement.lt/api/alerts",
  "events": [
    "sensor.threshold.exceeded",
    "traffic.congestion.detected"
  ],
  "filters": {
    "location": ["district-5", "district-6"],
    "severity": ["high", "critical"]
  },
  "headers": {
    "X-API-Key": "city_traffic_system_key_123"
  },
  "secret": "webhook_signing_secret_456",
  "active": true
}

// Response
{
  "status": "success",
  "data": {
    "webhook_id": "wh_7f9a8b7c6d5e",
    "name": "Traffic Alert Notification",
    "target_url": "https://traffic.citymanagement.lt/api/alerts",
    "events": [
      "sensor.threshold.exceeded",
      "traffic.congestion.detected"
    ],
    "created_at": "2025-01-21T14:32:10Z",
    "status": "active"
  }
}

Integration Process

Our structured approach to integration ensures smooth connectivity between your existing systems and our platform.

Step-by-Step Integration

  1. Discovery & Requirements:

    We begin with a thorough assessment of your existing systems, data flows, and integration objectives to create a detailed integration plan.

  2. Architecture Design:

    Our integration architects design a solution that addresses your specific requirements, considering performance, security, and scalability needs.

  3. Development & Testing:

    We implement the integration components and conduct comprehensive testing in a sandbox environment to ensure reliability.

  4. Deployment & Validation:

    The integration is deployed to production with careful monitoring and validation to confirm proper operation.

  5. Documentation & Training:

    We provide detailed documentation and training for your team to manage and maintain the integration.

Integration Best Practices

  • Security-First Approach:

    All integrations implement comprehensive security measures, including encryption, authentication, and regular security reviews.

  • Resilient Design:

    Integrations are designed with fault tolerance in mind, including retry mechanisms, circuit breakers, and graceful degradation.

  • Performance Optimization:

    We optimize data transfer patterns to minimize latency and bandwidth consumption, particularly for resource-constrained environments.

  • Monitoring & Alerting:

    Comprehensive monitoring ensures integration health is continuously assessed, with alerts for any anomalies.

  • Versioning & Compatibility:

    Clear versioning strategies ensure smooth updates and backward compatibility for critical integrations.

Ready to Integrate?

Contact our integration team to discuss your specific requirements and explore how our platform can connect with your existing systems.

Contact Integration Team