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Additional Options & Services for Sensor Networks

Enhance your IoT deployment with specialized services and configurations tailored to your smart city's unique requirements.

Edge Computing Packages

Deploy intelligent processing capabilities at the network edge to reduce latency, conserve bandwidth, and enable autonomous operation even during connectivity interruptions.

Light Package

Ideal for distributed sensor networks with basic local processing needs and limited hardware resources.

Features

  • Basic data filtering and validation
  • Simple aggregation functions (min, max, avg)
  • Store-and-forward during connectivity loss
  • Lightweight container (< 100MB footprint)
  • Supports ARM/x86 architectures

Smart City Applications

  • Environmental monitoring sensors
  • Waste bin fill level monitoring
  • Simple traffic counters
  • Street lighting control

Standard Package

Balanced solution for mid-range deployments requiring more sophisticated edge intelligence and data processing capabilities.

Features

  • Advanced filtering with multi-condition rules
  • Complex statistical functions and anomaly detection
  • Local time-series database (7-30 day retention)
  • Basic machine learning inference engine
  • Local API for direct data access

Smart City Applications

  • Traffic intersection management
  • Air quality monitoring stations
  • Public transportation hubs
  • Smart parking systems

Enterprise Package

Comprehensive edge computing solution for mission-critical deployments requiring maximum local intelligence and autonomy.

Features

  • Full edge analytics suite with custom processing pipelines
  • Advanced ML model deployment and training
  • Distributed computing across edge node clusters
  • High-availability configuration with failover
  • Edge-to-edge mesh networking with data sharing

Smart City Applications

  • Intelligent traffic management systems
  • Emergency response coordination
  • Multi-modal transportation hubs
  • Critical infrastructure monitoring

Edge Deployment Architecture

Wide view of a smart city district showing the strategic deployment of edge computing nodes with visible connectivity between nodes and sensors

Hierarchical Edge Topology

Our edge computing architecture implements a hierarchical approach that distributes intelligence across multiple tiers:

  • Tier 1 (Sensor Level): Lightweight processing directly on sensor devices for initial filtering and compression
  • Tier 2 (Gateway Level): Aggregation nodes that collect data from multiple sensors and perform intermediate processing
  • Tier 3 (District Level): Higher-capacity edge servers that implement sophisticated analytics and coordination across multiple gateways
  • Tier 4 (City Level): Central processing infrastructure for cross-district analysis and long-term storage

Edge Deployment Benefits

Implementing edge computing in your smart city deployment provides numerous advantages:

  • Reduced Latency: Critical processing occurs closer to data sources, enabling real-time responses
  • Bandwidth Conservation: Only relevant, processed data is transmitted to the cloud, reducing network load
  • Enhanced Reliability: Systems continue functioning during connectivity interruptions
  • Privacy Protection: Sensitive data can be processed locally without transmission
  • Scalability: Processing capacity grows organically with sensor deployment

Data Retention & Storage Tiers

Implement intelligent data lifecycle management to balance accessibility, performance, and cost-effectiveness while meeting regulatory requirements.

Hot Storage Tier

High-performance storage for recent data requiring frequent access and real-time analytics.

Characteristics

  • Full-resolution data retention
  • Sub-millisecond query response
  • In-memory processing capabilities
  • Typical retention: 7-30 days

Use Cases

  • Real-time dashboards and monitoring
  • Anomaly detection and alerting
  • Operational decision making
  • Pattern recognition in recent data

Warm Storage Tier

Balanced storage solution for intermediate-term data with moderate access frequency and analytical needs.

Characteristics

  • Downsampled data with intelligent aggregation
  • 10-100ms query response
  • Optimized compression algorithms
  • Typical retention: 1-6 months

Use Cases

  • Trend analysis and reporting
  • Comparative performance evaluation
  • Seasonal pattern recognition
  • Medium-term forecasting

Cold Storage Tier

Cost-effective long-term storage for historical data with infrequent access requirements and archival purposes.

Characteristics

  • Highly compressed with multiple aggregation levels
  • Second to minute query response
  • Immutable storage options for compliance
  • Typical retention: 1-7+ years

Use Cases

  • Regulatory compliance and auditing
  • Long-term trend analysis
  • Historical benchmarking
  • Machine learning model training

Custom Retention Policies

Our platform enables you to define granular retention policies based on data characteristics, importance, and regulatory requirements:

Policy Parameters

  • Data Category: Different retention rules for different types of data (environmental, traffic, security, etc.)
  • Importance Level: Longer retention for critical measurements vs. routine readings
  • Downsampling Rules: Custom aggregation functions and intervals for each data category
  • Compliance Requirements: Special handling for data subject to regulatory retention mandates
  • Access Patterns: Optimization based on typical query and analysis patterns

Implementation Example

// Retention Policy Configuration Example

{
  "policies": [
    {
      "name": "traffic_data",
      "match": {
        "sensor_type": "traffic",
        "location_type": ["intersection", "highway"]
      },
      "tiers": [
        {
          "tier": "hot",
          "retention": "30d",
          "resolution": "full"
        },
        {
          "tier": "warm",
          "retention": "90d",
          "resolution": "5m",
          "aggregation": ["avg", "max", "count"]
        },
        {
          "tier": "cold",
          "retention": "3y",
          "resolution": "1h",
          "aggregation": ["avg", "max", "count"]
        }
      ]
    },
    
    {
      "name": "environmental_data",
      "match": {
        "sensor_type": ["air_quality", "temperature", "humidity"]
      },
      "tiers": [
        {
          "tier": "hot",
          "retention": "7d",
          "resolution": "full"
        },
        {
          "tier": "warm",
          "retention": "180d",
          "resolution": "15m",
          "aggregation": ["avg", "min", "max"]
        },
        {
          "tier": "cold",
          "retention": "5y",
          "resolution": "1h",
          "aggregation": ["avg", "min", "max"]
        }
      ]
    }
  ]
}

Custom Analytics & ML Pipelines

Extend the platform's capabilities with specialized analytics and machine learning solutions tailored to your specific smart city challenges.

Advanced Analytics Services

Our data science team can develop custom analytics solutions that extract maximum value from your sensor data:

Anomaly Detection Systems

Sophisticated algorithms to identify unusual patterns and potential issues:

  • Multi-variate Anomaly Detection: Identify abnormal conditions across multiple related sensors
  • Contextual Anomalies: Detect anomalies that consider time, location, and environmental factors
  • Collective Anomalies: Recognize unusual patterns across sensor groups
  • Confidence Scoring: Prioritize alerts based on anomaly certainty

Predictive Maintenance

Anticipate equipment failures before they occur to optimize maintenance schedules:

  • Failure Prediction Models: Estimate remaining useful life of infrastructure components
  • Maintenance Optimization: Balance maintenance costs against failure risks
  • Component-specific Models: Specialized algorithms for different infrastructure types
  • Condition-based Monitoring: Adaptive thresholds based on operating conditions

Machine Learning Pipeline Development

End-to-end ML solutions from data preparation to model deployment and monitoring:

Custom Model Development

  • Traffic Flow Prediction: Forecast congestion patterns hours in advance
  • Environmental Impact Analysis: Model pollution dispersion and concentration
  • Resource Optimization: Optimize resource allocation for city services
  • Behavioral Pattern Recognition: Identify usage patterns for infrastructure planning

MLOps Infrastructure

Comprehensive infrastructure for the complete ML lifecycle:

  • Automated Model Training: Scheduled retraining with new data
  • Model Versioning: Track model lineage and performance
  • A/B Testing Framework: Validate model improvements before deployment
  • Model Monitoring: Track drift and performance degradation
  • Distributed Inference: Deploy models across edge and cloud

Traffic Optimization

Advanced analytics for traffic management and optimization in urban environments.

Key Capabilities

  • Real-time congestion prediction
  • Adaptive signal control algorithms
  • Origin-destination analysis
  • Multi-modal transportation optimization

Environmental Intelligence

Comprehensive environmental monitoring and analysis for urban sustainability.

Key Capabilities

  • Pollution source identification
  • Air quality forecasting models
  • Urban heat island analysis
  • Climate resilience planning tools

Energy Efficiency

Advanced analytics for optimizing energy usage across urban infrastructure.

Key Capabilities

  • Demand forecasting and management
  • Building energy optimization
  • Grid load balancing algorithms
  • Renewable integration optimization

SLA & Support Options

Choose the right level of support and service guarantees to ensure your smart city infrastructure operates reliably and efficiently.

Standard Support

Essential support for non-critical deployments with basic service level guarantees.

Service Level Agreements

  • 99.5% platform availability
  • 8-hour response time for critical issues
  • Next business day for standard issues
  • Business hours support (9am-5pm EET)

Support Channels

  • Email support
  • Online knowledge base
  • Community forums
  • Monthly system status reports

Enhanced Support

Comprehensive support for important deployments requiring higher reliability and faster response times.

Service Level Agreements

  • 99.9% platform availability
  • 4-hour response time for critical issues
  • 8-hour response for standard issues
  • Extended support hours (7am-9pm EET)

Support Channels

  • Email and phone support
  • Dedicated support portal
  • Quarterly review meetings
  • Advanced monitoring and alerting
  • Prioritized issue resolution

Premium Support

Mission-critical support for essential smart city infrastructure requiring maximum reliability and personalized assistance.

Service Level Agreements

  • 99.99% platform availability
  • 1-hour response time for critical issues
  • 4-hour response for standard issues
  • 24/7/365 support coverage

Support Channels

  • Dedicated technical account manager
  • Direct access to senior engineers
  • Monthly executive briefings
  • Proactive system monitoring
  • Custom health checks and alerts
  • Priority escalation path

Monitoring & Incident Management

Proactive Monitoring

Our support packages include comprehensive monitoring to detect and address issues before they impact your operations:

  • System Health Monitoring: Continuous tracking of platform components and services
  • Performance Metrics: Detailed visibility into system performance and resource utilization
  • Anomaly Detection: Automated identification of unusual patterns that may indicate problems
  • Predictive Alerts: Early warning system for potential issues based on trend analysis
  • Security Monitoring: Continuous surveillance for potential security threats

Incident Response Process

Our structured approach to incident management ensures rapid resolution with minimal impact:

  1. Detection & Classification: Immediate identification and severity assessment
  2. Notification: Automated alerts to appropriate support personnel
  3. Initial Response: Acknowledgment and preliminary investigation
  4. Diagnosis: Root cause analysis and impact assessment
  5. Resolution: Implementation of fix or workaround
  6. Recovery: Restoration of normal service operation
  7. Post-Incident Review: Analysis and preventive measures

Deployment Models

Choose from flexible deployment options to meet your specific operational, security, and compliance requirements.

Cloud Deployment

Fully managed SaaS solution hosted in secure cloud infrastructure with rapid deployment and minimal maintenance.

Key Features

  • Rapid deployment (typically 1-2 weeks)
  • Automatic updates and maintenance
  • Elastic scaling based on demand
  • EU-based data centers (Lithuania)
  • Predictable subscription pricing

Best For

  • Organizations seeking rapid deployment
  • Projects with limited IT resources
  • Deployments requiring flexible scaling
  • Standard compliance requirements

Hybrid Deployment

Balanced approach combining cloud management with on-premises data processing for sensitive information.

Key Features

  • Data processing at the edge or on-premises
  • Cloud-based management and analytics
  • Configurable data residency policies
  • Secure VPN connectivity
  • Moderate deployment complexity

Best For

  • Organizations with data sovereignty requirements
  • Projects with mixed sensitivity data
  • Environments with connectivity constraints
  • Phased cloud migration strategies

On-Premises Deployment

Complete platform deployment within your own infrastructure for maximum control, security, and compliance.

Key Features

  • Full data sovereignty and control
  • Integration with existing security systems
  • Air-gapped deployment options
  • Custom hardware optimization
  • Higher deployment complexity

Best For

  • Critical infrastructure monitoring
  • Strict regulatory environments
  • High-security requirements
  • Organizations with existing data centers
  • Specialized hardware requirements

Compliance Considerations for LT/EU Deployments

Our deployment models are designed to help you meet Lithuanian and European Union regulatory requirements:

Data Protection & Privacy

  • GDPR Compliance: All deployment models support GDPR requirements with appropriate technical and organizational measures
  • Data Minimization: Configurable data collection policies to implement privacy by design
  • Purpose Limitation: Granular controls over data usage and processing
  • Storage Limitation: Automated data lifecycle management with configurable retention policies
  • Security Measures: Comprehensive security controls aligned with GDPR Article 32 requirements

Sector-Specific Compliance

  • Critical Infrastructure: Compliance with NIS2 Directive requirements for critical infrastructure protection
  • Public Sector: Alignment with Lithuanian public sector data management regulations
  • Smart City Standards: Support for emerging EU standards for smart city deployments
  • Environmental Monitoring: Compliance with EU environmental monitoring and reporting requirements
  • Telecommunications: Alignment with EU Electronic Communications Code requirements for IoT deployments

Ready to Enhance Your Smart City Deployment?

Contact our team to discuss your specific requirements and create a tailored solution package.