Distributed Mobile Automation & Data Platform
A distributed automation platform designed to coordinate physical Android devices, execute scheduled application workflows, collect structured operational data, validate results, and maintain controlled execution across a large mobile environment.
Large-scale mobile execution engineered as an operational system.
The system was designed for mobile workflows that could not depend on manual execution.
Multiple physical Android devices had to remain available for scheduled application workflows, maintain controlled session state, execute multi-step interactions, capture structured results, and provide enough operational visibility to identify failures without stopping the wider execution environment.
The resulting architecture combined device control, mobile automation, scheduling, data collection, validation, recovery, and operational monitoring as one system.
Execution remains controlled as work spreads.
- 01Workload
A scheduled workload enters the controlled execution environment.
- 02Allocation
The orchestration layer selects available devices as execution resources.
- 03Execution
Allocated devices move through independent synthetic application stages.
- 04Parallel activity
Multiple workflows progress concurrently rather than as one linear sequence.
- 05Failure isolation
Evidence is preserved and one invalid application state is reset, retried, or isolated while healthy work continues.
- 06Data convergence
Structured results return from active devices to the central data pipeline.
- 07Validation
Valid records continue while an illustrative invalid record is isolated.
- 08Structured output
Accepted results become a controlled operational dataset and visible completion state.
Coordinating mobile execution beyond a single device.
Single-device automation is relatively straightforward. Distributed physical-device automation introduces a different class of engineering problem. Device availability, application state, session isolation, scheduling, connectivity, timing, interface changes, incomplete workflows, validation, data integrity, failures, and structured result collection all have to be managed without allowing one device to collapse unrelated execution.
Principles designed into the system.
The architecture treats operation, failure, and evidence as first-class concerns.
Device allocation
Available devices are treated as execution resources rather than assuming every device is always ready.
State-aware execution
Automation reacts to application and device state instead of blindly reproducing fixed taps.
Session isolation
Execution state is separated so one workflow does not contaminate another.
Validation before acceptance
A completed interaction is not automatically treated as valid output.
Failure isolation
Recoverable failures can retry while unhealthy devices or workflows can be isolated.
Observable operations
Execution state, validation, and failure evidence remain visible to operators.
Designed for devices that do not always behave perfectly.
Physical devices disconnect. Applications change state. Interfaces load slowly. Sessions expire. Networks fail. Individual workflows can return incomplete results. The automation architecture was designed around those realities by combining state checks, controlled retries, validation, isolation, and operational visibility.
Tools selected around the operational system.
Technologies shown reflect the engineering landscape; individual components use only what their role requires.
This project demonstrates PiBert’s ability to combine physical-device automation, distributed execution, data engineering, validation, and operational reliability within one controlled system.
Client identity and selected operational details have been withheld to preserve confidentiality. The architecture shown has been abstracted while retaining the engineering principles of the delivered system.