IoT & Edge
Field telemetry to enterprise — connecting the physical and digital.
IoT engineering bridges the physical world and enterprise intelligence systems. TDS Global designs and builds end-to-end connected systems — from field device integration and edge computing to cloud ingestion, time-series analytics and operational intelligence platforms — engineered for reliability in demanding physical environments.
How we approach iot & edge.
IoT systems fail where software systems can be redeployed: on the factory floor, in the field, on a vessel or inside clinical equipment. Resilience in IoT is an engineering discipline, not a feature — it requires offline-first edge logic, graceful degradation, secure device management and data pipelines that handle the unreliability of physical networks. We build for environments where connectivity is intermittent and hardware replacement is expensive.
Specific deliverables within this capability.
IoT Architecture Design
End-to-end system blueprints covering device selection, edge gateway architecture, connectivity protocols, cloud ingestion, storage and application layers.
Edge Computing
On-device and gateway-level intelligence — local processing, ML inference at the edge, offline buffering and selective cloud sync for bandwidth-constrained environments.
Device Fleet Management
Secure device provisioning, OTA firmware update management, certificate rotation and remote diagnostic capability for large device fleets.
Real-Time Telemetry Pipelines
High-throughput time-series data ingestion from thousands of sensors to cloud platforms with exactly-once delivery semantics and data quality validation.
Operational Intelligence Dashboards
Real-time monitoring interfaces displaying asset health, production metrics and environmental conditions with threshold alerting and drill-down capability.
Edge ML & Anomaly Detection
TensorFlow Lite and ONNX-based ML models deployed to edge devices for real-time anomaly detection, quality inspection and predictive classification.
How we execute every iot & edge engagement.
Physical Environment Assessment
We assess connectivity, power, operating conditions, existing protocols and integration requirements before designing any system architecture.
Protocol & Connectivity Design
MQTT, OPC-UA, Modbus or proprietary protocol integration is designed before cloud architecture — the physical layer constrains everything above it.
Edge Architecture
Edge gateway and device logic is designed for offline resilience — systems must function when connectivity is lost, syncing when it returns.
Cloud Platform Integration
Time-series storage, stream processing and application APIs are built to handle the volume, velocity and variability of IoT data.
Fleet Operations
Device management, OTA update pipelines and remote diagnostic tooling are delivered alongside the system — operational capability, not just connectivity.
How you know we do this well.
These are the specific engineering practices and standards that distinguish our work — not claims, but verifiable commitments baked into every engagement.
We design for offline-first: edge systems buffer data and operate independently when cloud connectivity is lost
Device fleet management — OTA updates, certificate rotation, remote diagnostics — is a deliverable, not an afterthought
We select protocols (MQTT, OPC-UA, Modbus, AMQP) based on the physical environment and existing equipment — not by convention
Our time-series data pipelines are designed for the specific volume and velocity of the target fleet — not generic templates
Edge ML models we deploy are validated against production data before deployment, with version control and rollback capability
We include cybersecurity design for IoT: device identity, certificate management, network segmentation and encrypted communication from initial architecture
What gets delivered.
Measurable engineering outcomes our practice delivers consistently across client engagements.
Real-time visibility across distributed physical assets replacing manual inspection rounds
15–25% reduction in equipment downtime through edge-based predictive maintenance
Data pipeline reliability >99.5% despite intermittent field connectivity
OTA firmware updates deployed across device fleets without manual field intervention
Operational intelligence dashboards driving measurable improvements in maintenance and production decisions
Tools & platforms we use.
Bring IoT & Edge capability into your organisation.
Our practice leads are available to discuss your specific technical challenges and what a scoped engagement would look like.