Custom shield

Smart Bird Cage Automation System

Open-source firmware, circuit schematics, and mechanical integration for an autonomous IoT bird cage management system. This platform consolidates solid feed dispensing, liquid water monitoring and replenishment, and a single-axis linear brush-and-spray tray cleaning mechanism orchestrated by an Arduino Uno R4 WiFi.

Publication Reference

If you use this system, codebase, or hardware design in academic work, please cite the original peer-reviewed publication:

M. F. Rahman, M. K. Anam, N. F. Arfa, F. Husnayain, and R. Suwandi, "Integration of Sensor-Based IoT Automation for Feeding and Cleaning in Smart Bird Cage Systems," Jurnal Otomasi Kontrol dan Instrumentasi, vol. 18, no. 1, pp. 83–92, 2026. DOI: 10.5614/joki.2026.18.1.7

@article{rahman2026smartbirdcage,
  title     = {Integration of Sensor-Based IoT Automation for Feeding and Cleaning in Smart Bird Cage Systems},
  author    = {Rahman, Muhammad Farid and Anam, Muhammad Khoirul and Arfa, Nuril Fathara and Husnayain, Faiz and Suwandi, Rifki},
  journal   = {Jurnal Otomasi Kontrol dan Instrumentasi},
  volume    = {18},
  number    = {1},
  pages     = {83--92},
  year      = {2026},
  doi       = {10.5614/joki.2026.18.1.7},
  url       = {https://doi.org/10.5614/joki.2026.18.1.7}
}

System Overview & Architecture

Conventional avian care systems focus solely on feeding or employ mechanically complex conveyor belts that struggle with dried waste. This architecture introduces three key improvements:

1. Differentiated Sensing: An ultrasonic sensor measures dry feed, while a non-contact capacitive strip tracks water depth—bypassing acoustic distortion in humid, confined spaces.
2. Integrated Mechanical Sanitation: A lead-screw-driven linear brush paired with a water spray routine dislodges adhered droppings.
3. Hybrid Scheduling & Failsafes: Operates via Arduino IoT Cloud telemetry while retaining high-precision offline schedule execution through an onboard DS3231SN Real-Time Clock (RTC).

flowchart TD
    subgraph Layer1["Physical Layer (Cage, Sensors & Actuators)"]
        HC["HC-SR04 Ultrasonic Sensor<br/>(Solid Feed Level)"]
        CAP["Grove Capacitive Sensor (10 cm)<br/>(Water Reservoir Level)"]
        DHT["DHT11 Sensor<br/>(Ambient Temp & Humidity Telemetry)"]
        RTC["DS3231SN RTC Module<br/>(I2C Offline Clock)"]
        
        SERVO["MG996R Servo Motor<br/>(Food Gate Flap)"]
        SOL1["ZE-4F180 Solenoid Valve 1<br/>(Cleaning Tray Flush Water)"]
        SOL2["ZE-4F180 Solenoid Valve 2<br/>(Drinking Water Replenishment)"]
        STEPPER["NEMA 17 Stepper + A4988<br/>(Linear Cleaning Brush)"]
    end

    subgraph Layer2["Control & Processing Layer"]
        MCU["Arduino Uno R4 WiFi<br/>(RA4M1 Core + ESP32-S3 Coprocessor)"]
    end

    subgraph Layer3["Network & Cloud Layer"]
        CLOUD["Arduino IoT Cloud Broker<br/>(REST / MQTT over TLS)"]
    end

    subgraph Layer4["Application Layer"]
        DASH["Web Dashboard & Mobile App<br/>(Remote Monitor & Overrides)"]
    end

Hardware Bill of Materials (BOM)

[!NOTE] The custom PCB shield includes footprints and pull-ups for the DHT11 sensor. While DHT11 readings are captured and streamed to the Arduino IoT Cloud dashboard for ambient climate telemetry, the automation control logic (feeding and cleaning cycles) operates strictly based on ultrasonic, capacitive, and RTC time inputs as presented in the paper.

Software Flow & Control Logic

The firmware runs a deterministic, cyclic state-machine loop incorporating safety timeouts inspired by critical software engineering principles (e.g., NASA "Power of Ten" Rule #2).

flowchart TD
    Start([System Start / Loop]) --> ReadSensors[Read Sensors:<br/>HC-SR04, Capacitive Strip, DHT11 & RTC]
    ReadSensors --> SyncCloud[Push Telemetry to Arduino IoT Cloud]

    SyncCloud --> CheckFood{Food Level <= 25%?}
    CheckFood -- Yes --> OpenFoodGate[Move MG996R Servo to 180°]
    OpenFoodGate --> FoodLoop{Food Level > 95%<br/>OR Timeout > 10s?}
    FoodLoop -- Yes --> CloseFoodGate[Return Servo to 0°]
    FoodLoop -- No --> WaitFood[Loop Read Food Sensor] --> FoodLoop
    CloseFoodGate --> CheckWater
    CheckFood -- No --> CheckWater{Water Level <= 25%?}

    CheckWater -- Yes --> OpenWaterValve[Energize SOL_2 Refill Valve]
    OpenWaterValve --> WaterLoop{Water Level > 95%<br/>OR Timeout > 10s?}
    WaterLoop -- Yes --> CloseWaterValve[De-energize SOL_2 Refill Valve]
    WaterLoop -- No --> WaitWater[Loop Read Water Sensor] --> WaterLoop
    CloseWaterValve --> CheckRTC
    CheckWater -- No --> CheckRTC{Hour == 15:00<br/>AND Hour != LastChecked?}

    CheckRTC -- Yes --> RunCleaning[Execute Linear Cleaning Routine:<br/>Energize SOL_1 + Run Stepper back-and-forth<br/>8200 steps x cleaner_rep]
    RunCleaning --> CycleEnd([End of Loop Cycle])
    CheckRTC -- No --> CycleEnd

    CycleEnd -->|Yield / Loop Delay| Start

Safety Failsafe

Every automated refill subroutine is bound by a strict 10-second timeout ceiling. If a sensor reading fails, detaches, or experiences boundary chattering, the valve/servo forces closed automatically after 10 seconds to avoid overflow or seed spilling.

Calibration and Sensor Metrics

1. Solid Feed Level Calibration (Ultrasonic HC-SR04)

The sensor is mounted orthogonally at the top center of the seed container:

• Empty Distance ($D_{max}$): 18 cm $\rightarrow$ 0%
• Full Distance ($D_{min}$): 0 cm $\rightarrow$ 100%
• Trigger Threshold (25%): 13.5 cm
• Shut-off Threshold (95%): 0.9 cm

$$\text{Feed Level (%)} = \left( \frac{18 - D_{\text{measured}}}{18} \right) \times 100%$$

2. Water Level Calibration (Capacitive Grove Sensor)

The 10 cm capacitive sensor provides discrete height sensing over internal sensing segments:

• Resolution: 5 mm per segment step.
• Conversion: Scaled by a 5% step factor per active segment.
• Eliminates the sound-speed shifts and corrosion common to immersed acoustic sensors in high-humidity micro-climates.

Experimental Validation & Performance

The prototype was tested under controlled conditions ($27^\circ\text{C}$, 65% RH) across four validation axes:

pie title Dynamic Refill Failure Rates (n = 5 trials each)
    "Grove Capacitive Sensor (0% Failure)" : 100
    "HC-SR04 Ultrasonic Sensor (20% Failure)" : 20
    "HC-SR04 Successful Refills" : 80

1. Water Reservoir Accuracy:

   • Mean Absolute Error: 0.38 cm (maximum error $\le$ 0.5 cm).
   • Refill Failure Rate: 0% (0 / 5 trials).

2. Food Dispenser Accuracy:

   • Mean Absolute Error: 0.75 cm.
   • Refill Failure Rate: 20% (1 / 5 trials) due to echo bounce and signal chattering near the 25% threshold boundary. (Resolved by adding a debounce window in firmware).

3. Sanitation & Waste Removal Efficiency:

   • Evaluated across 100 discrete test sectors ($10 \times 10$ surface matrix) on dried bird droppings.
   • Quantitative waste removal efficiency reached 94% within a single cleaning cycle ($E_C = \frac{100 - 6}{100} \times 100%$).

Repository Structure

├── pcb-design/
│   ├── Fab/                     # Manufacturing gerbers & drill files
│   ├── components/              # KiCad 3D models & footprints
│   ├── exports/                 # PDF schematics and board plots
│   ├── custom-shield.kicad_sch  # KiCad 8 schematic design
│   ├── custom-shield.kicad_pcb  # KiCad 8 PCB layout
│   └── custom-shield.kicad_pro  # KiCad project file
├── src/
│   ├── src.ino                  # Main Arduino Uno R4 WiFi firmware
│   ├── arduino_secrets.h.example# Template for Wi-Fi credentials
│   └── thingProperties.h       # (Generated by Arduino IoT Cloud, git-ignored)
├── system-flowchart.png         # System flow chart diagram
├── CITATION.cff                 # GitHub native citation metadata
├── references.bib               # BibTeX citation entry
├── LICENSE                      # Creative Commons License
└── README.md                    # Project documentation

Setup & Getting Started

1. Hardware Connections

• HC-SR04 Ultrasonic: VCC $\rightarrow$ 5V, GND $\rightarrow$ GND, TRIG $\rightarrow$ Pin D7, ECHO $\rightarrow$ Pin D8
• DHT11 Sensor: VCC $\rightarrow$ 5V, GND $\rightarrow$ GND, DATA $\rightarrow$ Pin D13
• Grove Capacitive Sensor: Connect to I2C lines (SDA $\rightarrow$ A4 / SDA, SCL $\rightarrow$ A5 / SCL)
• DS3231SN RTC: Connect to common I2C bus (SDA, SCL)
• MG996R Servo: Signal $\rightarrow$ Pin D11, Power $\rightarrow$ External 5V rail
• ZE-4F180 Solenoid 1 (SOL_1, Cleaning Flush): Driven via TIP120 through Pin D3
• ZE-4F180 Solenoid 2 (SOL_2, Drinking Refill): Driven via TIP120 through Pin D4
• A4988 Stepper Driver: STEP $\rightarrow$ Pin D5, DIR $\rightarrow$ Pin D6, powered by 12V supply

2. Secrets & Wi-Fi Configuration

1. Copy the secrets template in src/:

   cp src/arduino_secrets.h.example src/arduino_secrets.h

2. Open src/arduino_secrets.h and provide your local network credentials:

   #define SECRET_SSID "YOUR_WIFI_SSID"
   #define SECRET_OPTIONAL_PASS "YOUR_WIFI_PASSWORD"

3. Arduino IoT Cloud Configuration

[!IMPORTANT] src/thingProperties.h is automatically generated by the Arduino IoT Cloud environment and is intentionally excluded from Git tracking to avoid credential/Thing ID collisions.

1. Create an account on Arduino IoT Cloud.
2. Create a new Thing and associate your Arduino Uno R4 WiFi device.
3. Configure the following cloud variables within the Thing dashboard:

4. When editing or deploying via the Arduino Cloud Web Editor or Arduino IDE with the Cloud plugin, thingProperties.h will be auto-populated and linked to your sketch. Flash src/src.ino to the board.

License

This project and associated documentation are distributed under the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) license.