Connected device IoT applications.
We build IoT applications connecting hardware devices to cloud platforms with real-time data streaming, device management, and intelligent analytics dashboards.
// MQTT Client Subscription in TypeScript
import mqtt from "mqtt";
const client = mqtt.connect("mqtts://broker.iot.aws");
client.on("connect", () => {
client.subscribe("devices/+/telemetry", { qos: 1 });
console.log("Connected to IoT broker");
});
client.on("message", (topic, payload) => {
const data = JSON.parse(payload.toString());
processDeviceTelemetry(topic, data);
});
function processDeviceTelemetry(topic: string, data: any) {
const deviceId = topic.split("/")[1];
storeTelemetry(deviceId, data);
checkAlertThresholds(deviceId, data);
}Device Communication Layer
Implementing lightweight IoT protocols like MQTT and BLE for efficient device-to-cloud communication with minimal power consumption and reliable message delivery across constrained networks.
Tools & Frameworks We Engineer With
Protocols
- MQTT: Lightweight publish-subscribe messaging protocol optimized for constrained IoT devices and low-bandwidth networks.
- CoAP: Constrained Application Protocol for resource-limited devices using UDP with RESTful interaction patterns.
- BLE: Bluetooth Low Energy for short-range device communication with minimal power consumption.
- WebSockets: Full-duplex communication channels for real-time browser-based IoT dashboards and control interfaces.
Cloud
- AWS IoT Core: Managed cloud service for secure device connectivity, message routing, and fleet management at scale.
- Azure IoT Hub: Enterprise IoT platform with device twins, direct methods, and integration with Azure analytics services.
- TimescaleDB: Time-series database optimized for IoT telemetry with hypertables and continuous aggregates.
- InfluxDB: Purpose-built time-series database with built-in downsampling and retention policies for sensor data.
Edge
- Raspberry Pi: Versatile single-board computer for IoT gateway applications with full Linux capabilities.
- ESP32: Low-cost microcontroller with integrated WiFi and Bluetooth for battery-powered IoT sensors.
- Arduino: Open-source hardware platform for rapid prototyping of sensor nodes and actuator controllers.
- Edge Computing: Local data processing at the network edge to reduce latency and bandwidth for time-critical IoT decisions.
Analytics
- Grafana: Open-source observability platform for creating real-time IoT dashboards with alerting capabilities.
- Apache Kafka: Distributed event streaming for high-throughput IoT data pipelines and real-time processing.
- TensorFlow Lite: Lightweight ML framework for on-device inference enabling predictive maintenance and anomaly detection.
- Predictive Maintenance: ML-driven failure prediction using sensor patterns to schedule maintenance before breakdowns occur.
Who We Work With
Smart Home
Connected home automation systems with voice control, energy management, and security monitoring across devices.
Industrial
IIoT solutions for factory automation, predictive maintenance, and real-time production line monitoring.
Healthcare Wearables
Medical-grade wearable devices for continuous patient monitoring, vital signs tracking, and remote diagnostics.
Agriculture
Smart farming solutions with soil sensors, automated irrigation, and crop health monitoring via drone integration.
Fleet & Logistics
Vehicle tracking, route optimization, and cold-chain monitoring for supply chain visibility and efficiency.
Energy & Utilities
Smart grid monitoring, renewable energy management, and utility meter reading automation at scale.
Our Delivery Lifecycle
We operate under a structured, predictable lifecycle. Click any step to inspect deliverables.
Device & Protocol Assessment
Evaluate hardware requirements, connectivity options, and communication protocols based on deployment environment constraints.
Protocol selection: MQTT over TLS for telemetry, BLE for local pairing. Gateway: Raspberry Pi 4 running Mosquitto broker with edge filtering.Frequently Asked
Protocol selection depends on device constraints, data frequency, and network environment. MQTT is ideal for reliable telemetry over TCP, CoAP suits extremely constrained devices over UDP, BLE works for short-range local communication, and WebSockets enable real-time browser dashboards. We evaluate power budget, bandwidth, and latency requirements to recommend the optimal protocol stack.
We implement defense-in-depth security: X.509 certificates for device authentication, TLS encryption for data in transit, secure boot for firmware integrity, and role-based access control for cloud APIs. Device credentials are rotated automatically, and we use AWS IoT Device Defender for continuous security auditing and anomaly detection.
Our architecture uses managed cloud IoT services (AWS IoT Core, Azure IoT Hub) that auto-scale to millions of concurrent connections. Time-series databases use hypertable partitioning for efficient writes, Kinesis handles burst ingestion, and edge computing offloads processing to reduce cloud load. We design for horizontal scaling from day one.
Over-the-air updates use signed firmware images distributed through AWS IoT Jobs. Devices check for updates on a configurable schedule, download delta patches to minimize bandwidth, verify cryptographic signatures, and apply updates with automatic rollback on failure. Fleet-wide rollouts use canary deployments to catch issues early.
Ready to build your IoT solution?
Get an IoT architecture proposal with device connectivity strategy and cloud platform design within one week.