Device plus firmware, dashboard, alert path, and pilot notes in a narrow scope.
IoT, embedded, edge AI, and automation engineering studio
We connect real-world devices to software.
MachineLoop builds practical IoT prototypes, sensor dashboards, hardware-to-cloud bridges, embedded firmware, edge-AI camera systems, control boxes, robotics integrations, and human-in-the-loop workflows for teams that need physical processes to become measurable, controllable, and visible.
ScopeBuildValidateHandoff
SenseSensors / cameras / equipment
BridgeESP32 / Raspberry Pi / MQTT
ActDashboard / alerts / controls
ESP32 prototype developmentRaspberry Pi IoT gatewayssensor monitoring dashboardsModbus to cloud bridgesserial device to MQTTmachine uptime monitoringedge AI camera prototypesJetson Nano object detectionOTA firmware updatesremote device diagnosticsrobotics sensor integrationESP32 prototype developmentRaspberry Pi IoT gatewayssensor monitoring dashboardsModbus to cloud bridgesserial device to MQTTmachine uptime monitoringedge AI camera prototypesJetson Nano object detectionOTA firmware updatesremote device diagnosticsrobotics sensor integration
Serial, Modbus, CAN-adjacent, logs, MQTT, APIs, and remote diagnostics.
Camera, audio, sensor, and local inference projects where cloud-only AI is not enough.
Heartbeat, logs, firmware version, update path, and fewer blind field visits.
Build packages
A service shelf for concrete hardware and automation work.
Inspired by the useful clarity of a shop, but built for custom engineering: each package has a narrow first scope, a useful deliverable, and a clear next step. Prices are starting points for small pilots; production hardware, certification, installation, and manufacturing are scoped separately.
IoT Prototype Sprint
ESP32 or Raspberry Pi device, firmware, sensor/control loop, dashboard or logs, alerts, wiring notes, BOM, and pilot risk list.
Best when the team needs a working proof before hiring hardware staff or funding a bigger build.Sensor Dashboard Kit
Temperature, humidity, vibration, leak, power, door, motion, air quality, or machine-state telemetry with history and alerts.
Best when a facility, lab, farm, workshop, or machine needs visible history instead of manual checks.Legacy Equipment Data Bridge
Serial, Modbus, CAN-adjacent, BLE, Wi-Fi, Ethernet, logs, MQTT, API handoff, dashboard, and remote diagnostics.
Best when useful machine data is trapped in old ports, vendor software, local logs, or spreadsheet exports.Edge AI Camera Prototype
Jetson-class or embedded Linux pipeline for camera/audio/sensor inference, event logs, alerts, and human review when confidence is low.
Best when cloud AI is not enough because the camera, audio, or decision loop belongs near the machine.OTA + Telemetry Upgrade
Device heartbeat, logs, firmware version, remote diagnostics, update workflow, rollback thinking, and release checklist.
Best when prototypes are leaving the bench and field support cannot depend on blind site visits.Robotics Demo Integration
ROS2-adjacent bring-up, camera/motor/sensor integration, part location, measurement, event detection, and demo handoff.
Best when a robot, actuator, or operator needs sensor-derived coordinates, measurements, or pass/fail events.What gets de-risked
Not just a board on a desk. A path toward a working system.
01physical signal
Sensors, cameras, audio, serial ports, relays, motors, or existing machine output.
02software bridge
Firmware, MQTT/API handoff, dashboard, logs, alerts, and failure notes.
03field thinking
Heartbeat, diagnostics, operator review, vendor handoff, and production risks.
Service details
The same packages, expanded into searchable service pages.
The homepage stays simple. The service pages carry the longer buyer language for search: ESP32 prototype development, Raspberry Pi gateway, sensor dashboard, Modbus to cloud, OTA firmware updates, Jetson Nano object detection, and more.
Prototype in weeks
IoT prototype sprint for ESP32 and Raspberry Pi
Fast IoT prototype builds for teams that need a physical device to monitor, control, log, alert, or connect a real-world process to software.
Read detailsTelemetry and alerts
Sensor monitoring dashboard and alerts
Sensor monitoring systems for temperature, humidity, vibration, leaks, power, doors, motion, air quality, machine status, and environmental conditions.
Read detailsDevice data bridge
Legacy equipment data bridge
Data bridges for existing machines, serial devices, Modbus equipment, CAN-adjacent systems, BLE devices, and local logs that need cloud dashboards or API handoff.
Read detailsField reliability
OTA and telemetry upgrade
Remote update, heartbeat, logging, diagnostics, and firmware release workflows for prototypes and deployed devices that should not require constant field visits.
Read detailsRobotics and measurement
Robotic guidance and measurement automation
Robotics support, camera-guided positioning, industrial measurement automation, dimensional inspection, part location, alignment checks, and machine-control handoff.
Read detailsAI with hardware
Edge AI camera and audio prototype
Camera, audio, and sensor intelligence on Jetson Nano-class devices, embedded Linux systems, and cloud-assisted AI workflows.
Read detailsAlso available
Industrial machine vision inspectionMachine vision inspection systems for factories, workshops, and custom machines that need cameras to detect, measure, read, count, classify, or verify parts automatically.Camera quality control systemsCamera-based quality control systems for finding missing parts, mistaken parts, assembly errors, print defects, surface flaws, alignment issues, and other visual production problems.Barcode, QR, OCR, and OCV reading systemsBarcode, QR code, OCR, and OCV reading systems for production lines, packaging, labels, serial numbers, printed characters, VIN-like identifiers, and traceability workflows.Object recognition, video tracking, counting, and classificationObject recognition and tracking in video for counting, classification, event detection, safety monitoring, inventory observation, plant monitoring, and machine-adjacent automation.Outsourced automation developmentFocused automation projects for teams that need AI connected to sensors, control logic, data logging, displays, alerts, dashboards, or actuator control without hiring a full-time embedded team.Human-in-the-loop AI operationsOperational workflows where AI agents can ask trained humans to inspect, verify, label, decide, or handle edge cases that software and sensors should not own alone.Custom embedded hardware designArchitecture and prototype design for embedded systems that combine MCUs, sensors, power, wiring, enclosures, connectivity, and firmware.Control boxes and test fixturesSmall control boxes, test rigs, data capture systems, and operator panels for labs, workshops, greenhouses, and machine-adjacent workflows.Prototype to vendor handoffTechnical scopes, BOMs, firmware prototypes, wiring notes, vendor packets, and implementation support for teams that need the physical build to keep moving.
Systems people search for
IoT monitoring, hardware-to-cloud, edge AI, and machine vision.
Many buyers do not search for abstract embedded systems. They search for sensor monitoring dashboards, ESP32 prototypes, Raspberry Pi gateways, machine uptime monitoring, camera quality control, OCR/OCV, barcode reading, edge AI detection, remote diagnostics, OTA updates, and robotics integration.
ESP32 sensor device plus dashboardRaspberry Pi industrial gatewayLegacy device data bridge with MQTT/API handoffOTA, heartbeat, logs, and device fleet visibilityMissing part and mistaken part detectionEdge AI camera, audio, and sensor event detection
Relevant project examples
Automation work across plants, cameras, control boxes, AI, and operators.
These examples combine hardware constraints with software, AI, and deployment thinking. That is where many automation projects fail: the model, sensor, enclosure, network, operator workflow, human fallback, and maintenance path are treated as separate problems.
Horticulture / Jetson Nano / custom ML
Horticulture ML: farm and greenhouse vision AI
Embedded OpenCV preprocessing and inference work on a custom ML model for horticulture monitoring and automation. The stack fits TensorFlow object detection and classification, OpenCV, AWS S3, Python, edge devices, and image capture workflows for clients trying to improve crop yield with better plant visibility.
A modern version can monitor canopy changes, plant stress, water-need signals, pests or insects, flower/fruit counts, growth-stage classification, and operator alerts. Jetson-class devices can run local inference while ESP32-class controllers connect sensors, valves, pumps, lights, fans, and greenhouse automation loops.
Sports video / GStreamer / AWS APIs
Automatic score follower for school sports video
Automatic score follower using AWS Media Live, NVIDIA Jetson Nano, ML models, and OpenCV. The useful pattern is edge video capture, GStreamer pipelines, local preprocessing, scoreboard region detection, score-change events, and cloud media workflows for live games.
A full pilot can track scoreboard digits, keep score event logs, generate overlays, mark clips around score changes, detect low-confidence frames, and ask an operator for review when glare, LED refresh, camera angle, or motion makes the score uncertain.
Control boxes / outsourced automation
Microcontrollers, sensors, operator panels, and data capture
Small control boxes with a microcontroller, sensor suite, Raspberry Pi or embedded Linux UI, CSV/data logging, and clear wiring so a one-off bench system can become a repeatable field unit.
AI integration / human-in-the-loop
Hardware systems that call AI, software, and people when useful
AWS, OpenAI, Claude, and local ML can sit behind cameras, microphones, sensors, and device telemetry. The goal is not AI decoration; it is better detection, summaries, alerts, configuration, operator support, and human escalation when confidence is low.
Field notes
Practical notes on industrial AI, machine vision, and embedded automation.
Short technical articles for teams evaluating what can be automated today with ESP32 and Raspberry Pi devices, sensors, MQTT gateways, dashboards, cameras, Jetson-class edge devices, industrial I/O, OTA, and AI-assisted review.
IoT prototypes
ESP32 and Raspberry Pi IoT prototype sprint
How to scope a practical IoT prototype: sensors, firmware, connectivity, dashboard, alerts, wiring notes, BOM, and prototype-to-pilot risks.
Read noteSensor dashboards
Sensor monitoring dashboard and alert systems
Practical sensor dashboards for environmental monitoring, machine status, leaks, vibration, power, facilities, greenhouses, workshops, and storage rooms.
Read noteHardware-to-cloud
Legacy equipment data bridge: Modbus, serial, CAN, and MQTT
How old equipment can send useful data to dashboards, APIs, databases, and remote diagnostics without replacing the whole machine.
Read noteField reliability
OTA, telemetry, and device fleet management for prototypes
Why deployed prototypes need heartbeat, logs, firmware version tracking, remote diagnostics, update paths, and clear release discipline.
Read noteHorticulture ML
Horticulture ML: greenhouse AI vision automation
How TensorFlow object detection, OpenCV preprocessing, AWS S3, Python, and edge devices can monitor crops, classify plant state, and support greenhouse automation.
Read noteSports video AI
Automatic scoreboard follower with Jetson Nano and AWS Media Live
A practical architecture for school sports video: camera ingest, GStreamer, Jetson Nano, OpenCV, ML models, AWS Media Live, score detection, and event-aware overlays.
Read noteMachine vision
Industrial machine vision inspection with AI and embedded systems
How camera inspection systems combine lighting, lenses, OpenCV, edge AI, Jetson-class devices, PLC signals, and human review for practical quality control.
Read noteVisual QC
Camera quality control for missing parts and assembly errors
A practical view of camera-based QC for missing screws, clips, sockets, labels, wrong parts, surface flaws, and final assembly checks.
Read noteTraceability
OCR, OCV, barcode, and QR reading on production lines
How production lines can read and verify labels, serial numbers, barcodes, QR codes, printed characters, and traceability data.
Read noteVideo intelligence
Object recognition, video tracking, counting, and classification
How video can become structured events: object detection, tracking, counting, classification, alerts, and operator review.
Read noteRobotics
Robotic guidance and camera measurement automation
Using cameras for robot guidance, part position, dimensional checks, alignment, distance, angle, diameter, and conveyor or PLC handoff.
Read noteGood fit
Best scopes are narrow, measurable, and useful after handoff.
MachineLoop is a good fit when you need an engineering studio to connect AI to the real world: a working IoT prototype, outsourced automation help, a device data bridge, a debug sprint, a firmware layer, a sensor and camera plan, a human-in-the-loop workflow, or a technical scope another vendor can build from. Larger PCB layout, certified manufacturing, enclosure production, and on-site installation can be coordinated with specialists when needed.
Start small
Send the automation brief.
A good first message includes current hardware, MCU or board, sensors, machine interface, camera/audio inputs, connectivity, what already works, what fails, who operates it, and what the system must do in the real world. If the device needs heartbeat, logs, OTA, alerts, or a dashboard, include that too.
Worldwide clients are welcome. Istanbul/Ankara-region physical installation can be discussed when the scope needs hands-on work.