Edge Device Status
Sensor Uptime99.6%
Predictive Maintenance Alerts96.3%
Anomaly Detection Accuracy98.1%
Edge Inference Latency<200ms
Connected Devices Online1,240+
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Service · IoT Integration

IoT That
Thinks
at the
Edge

From sensor data pipelines and edge AI to predictive maintenance and real-time anomaly detection — we connect your physical operations and digital systems with intelligence built in, not bolted on.

6
IoT Domains
25+
Years Exp.
50+
Clients
IoT Capabilities

Where Should Intelligence Live?

We work across the full IoT stack — from sensor to edge to cloud — selecting the right architecture for your latency, connectivity, and data requirements.

01
Sensor Data Pipelines
Real-time ingestion from industrial sensors, meters, and connected devices — structured, validated, and routed to the right systems for monitoring, analytics, or AI model input.
MQTT / OPC-UAReal-Time Ingestion
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02
Edge AI & Predictive Maintenance
On-device inference models that detect early signs of equipment failure from vibration, temperature, or usage-pattern data — flagging maintenance needs before a breakdown occurs.
On-Device InferenceFailure Prediction
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03
Anomaly Detection on Sensor Streams
Continuous, automated monitoring of live sensor data to catch unusual readings — leak detection, unsafe operating conditions, or equipment drift — in real time.
Real-Time AlertsDrift Detection
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04
Device Connectivity & Protocols
Integration across MQTT, Modbus, OPC-UA and other industrial protocols — connecting legacy machinery and modern sensors into a single data layer.
ModbusLegacy Integration
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05
IoT Dashboards & Alerting
Real-time operational dashboards and configurable alert rules, giving operations teams live visibility into distributed equipment and facilities.
Live DashboardsAlert Rules
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06
Industrial & Infrastructure Deployments
Field-proven deployment experience across manufacturing lines, utility infrastructure, and government facilities — from pilot to enterprise scale.
ManufacturingUtilities
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Our IoT Practice

Practical IoT Built for Industry

At Informatics India, we focus on applied IoT — connecting real equipment and facilities to real decisions. With a foundation in enterprise software engineering, we integrate sensor data and edge AI into production-grade systems that are reliable, maintainable, and secure.

Retrofits existing machinery — no rip-and-replace required
Edge inference for latency-sensitive, safety-critical alerts
Local data buffering — no readings lost during outages
On-premise, private cloud, or hybrid deployment
Human-in-the-loop escalation for high-stakes alerts
● Edge-First Engineering
IoT that fits your equipment, sites & teams
Our IoT solutions are engineered around your existing equipment and facilities — no forklift upgrade required. We connect to your sensors, gateways, and control systems to build monitoring that operates within your security and connectivity constraints.
25+
Years Software Expertise
6
IoT Capability Domains
50+
Enterprise Clients
5
Countries
What We Deliver

IoT Engineering Capabilities

End-to-end delivery from site assessment and connectivity through to production monitoring and long-term support.

Site & Equipment Assessment
On-site survey of existing equipment, sensors, and connectivity — identifying which assets can be retrofitted and which require new sensor hardware.
Connectivity & Protocol Design
Selecting and configuring the right mix of MQTT, Modbus, OPC-UA, and gateway hardware to bridge legacy machinery and modern sensors into one data layer.
Edge Model Training & Evaluation
Training predictive maintenance and anomaly-detection models on your historical sensor data, validated against real failure and incident records before deployment.
Edge & Cloud Deployment
Packaging trained models for on-device inference where latency matters, with cloud-based analytics and dashboards for less time-critical reporting.
Resilience & Offline Buffering
Local data buffering at the edge so readings are never lost during connectivity drops — a common requirement at remote industrial and government sites.
Ongoing Monitoring & Support
Continuous device health monitoring, alert-rule tuning, and model retraining as equipment ages and operating conditions change.
IoT Delivery Process

From Sensor to Insight

A structured, phased approach to deploying IoT that survives real industrial conditions — with visibility at every stage.

01
Site Survey & Feasibility

On-site assessment of equipment, existing sensors, connectivity, and environmental conditions to define the right architecture before any hardware is ordered.

02
Connectivity & Pilot Deployment

Sensor installation, protocol integration, and a limited pilot deployment to validate data quality and connectivity before scaling.

03
Model Training & Validation

Training predictive maintenance and anomaly-detection models on real sensor data, validated against actual failure and incident history.

04
Scale-Out & Monitoring

Rolling out to the full site or fleet, with dashboards, alerting, and ongoing monitoring to catch drift as equipment and conditions change.

● Enterprise IoT Partner
Built with industrial rigour
Our IoT solutions are built by software engineers with real industrial deployment experience — ensuring sensor pipelines and edge models are packaged, deployed, and maintained with the same rigour as production enterprise software.
6
IoT capability domains
25+
Years expertise
5
Countries served
50+
Enterprise clients
Technology Stack

Tools & Protocols

Production-proven IoT and edge technologies selected for reliability, latency, and industrial durability.

MQTT / Modbus / OPC-UA Edge Gateways (Raspberry Pi / Industrial) Python (Edge Inference) TensorFlow Lite / ONNX Runtime Time-Series Databases (InfluxDB) MQTT Brokers / Message Queues AWS IoT / Azure IoT Hub Grafana / Power BI Dashboards Vector & Time-Series Storage Docker / Kubernetes TLS / VPN Device Security LoRaWAN / Cellular IoT
Industries

Sectors We Apply IoT To

IoT is most valuable where equipment is distributed and downtime is costly — we've delivered across these industries.

Manufacturing
Production-line sensors
Energy & Utilities
Equipment monitoring
Government Infrastructure
Field sensor networks
Industrial Equipment
Predictive maintenance
Automobile
Assembly-line monitoring
Irrigation & Water Infra
Remote site telemetry
Logistics & Warehousing
Asset tracking
Facilities & Infrastructure
Condition monitoring
FAQ

Common Questions

Do we need to replace our existing machinery to use IoT sensors?
No — in most industrial deployments we retrofit sensors onto existing equipment and connect through industrial protocols like Modbus or OPC-UA, without requiring new machinery.
Does the AI/analysis run in the cloud or on the device itself?
Both models are supported. For latency-sensitive use cases like safety alerts, we run inference directly on edge hardware. For less time-critical analytics, data can be sent to the cloud for processing.
What happens if connectivity drops at a remote site?
Edge devices buffer data locally and sync once connectivity is restored, so no readings are lost during network outages — a common requirement at remote industrial and government sites.
How long does a typical IoT deployment take?
A pilot deployment on a limited set of equipment can typically be completed in a few weeks. Full-site or fleet-wide rollout timelines depend on the number of assets and connectivity conditions — we provide a detailed timeline after the site survey.
Can predictive maintenance models work with limited historical failure data?
Yes, though accuracy improves with more historical data. Where failure history is limited, we start with rule-based anomaly detection and refine toward predictive models as more data is collected in production.
Start Your IoT Project

Ready to Connect Your Operations?

Share your equipment landscape and connectivity constraints. We'll provide an honest assessment of what's feasible to retrofit — and a clear roadmap to get there.

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