Raspberry Pi Jobs

Every morning my iPhone has to be woken, a six-digit PIN entered, a work app opened, credentials typed, several form fields completed and a digital signature placed. I want that entire routine removed from my hands by a small desktop robot. Core flow • Wake the phone from sleep by pressing the side button. • Physically tap the screen to enter the PIN code—no Bluetooth, Face ID or Touch ID, just precise mechanical interaction. • Launch the target app, wait for it to load, populate the login screen and navigate onward until the signature page is reached and signed. I imagine a compact gantry or articulated arm driven by servos or steppers, guided by a microcontroller (Arduino, Raspberry Pi, or similar). Because the touch targets are fixed, a predefined set of c...

I need help connecting all my smart devices to a Raspberry Pi using Homebridge, and integrating them with Apple HomeKit. Requirements: - Connect lights, thermostats, security cameras, and any other smart devices. - Ensure compatibility with iOS devices. - Setup should allow control via Apple Home app. Ideal Skills & Experience: - Experience with Raspberry Pi and Homebridge. - Familiarity with Apple HomeKit and iOS integration. - Knowledge of various smart home devices and their configurations.

I want to turn a Raspberry Pi running CODESYS into a reliable industrial automation node. Your job is to create the complete control application in MATLAB / Simulink using Stateflow, generate the code, import it into CODESYS and prove that it runs in real time on the Pi. The target is an industrial process (details and I/O list come once we start). I need a clean, well-structured Simulink + Stateflow model that covers the sequencing, safety interlocks and regulation logic, then produces compilable CODESYS code without manual patching. Please map the I/O to the Pi’s GPIO or any supported extension modules exactly as documented, and include watchdog handling so the plant fails safe. Deliverables • Simulink/Stateflow model (.slx) • Generated source and export settings ...

I need an image classification AI model to run on a Raspberry Pi 4. This model will detect whether individuals are wearing PPE kits in static images. The primary application will be in industrial sites. Key Requirements: - The model should accurately classify images as 'PPE' or 'No PPE'. - It needs to be optimized for performance on Raspberry Pi 4. - The input will be static images, not live feeds or videos. Ideal Skills and Experience: - Proficiency in AI and image classification techniques. - Experience with model optimization for edge devices, especially Raspberry Pi. - Background in developing AI solutions for industrial applications is a plus. - Ability to deliver a robust and efficient model within budget constraints.

Required Functions – Custom Control PCB for Sweeper Machine 1. Brush Motor Control – 4 Nos, 100 W each (Independent ON/OFF & speed control) 2. Brush Up / Down Control – 4 Nos (Electric Actuators) 3. Brush Extend / Retract Control – 2 Nos (Electric Actuators) 4. Suction Motor Control – 1 No • ON / OFF • Speed control (PWM / Analog) 5. Suction Head Up / Down Control – 1 No (Electric Actuator) 6. Suction Hose / Litter Picker Mode Selection – 1 No • Actuator-based function switching 7. Filter Shaker Motor Control – 1 No 8. Hydraulic Gate Open / Close Control – 1 No 9. Dust Tank Lift / Lower Control – 1 No (Hydraulic) 10. Dust Suppression Water Pump Control – 1 No 11. High-Pressure Jet Pump Contro...

I’m building a smart irrigation setup that links a Raspberry Pi edge server with several ESP32 nodes in the field. Each ESP32 gathers data from soil-moisture probes, compact weather boards (temperature, humidity, barometric pressure), and inline flow meters, then reports everything wirelessly to the Pi for processing. Here’s what I need from you: • Python (Raspberry Pi) and MicroPython/C++ (ESP32) code that ingests the raw sensor streams, pushes them through an on-device model, and decides—within seconds—whether to start or stop the main pump and which solenoid valves to open. • An ML pipeline: training notebooks, a lightweight model (TensorFlow Lite or similar) and the inference wrapper that runs locally. The model must act on current soil-moisture rea...

It is 2 stage project 'I have the source code available, i have the API dataset available. But definately need a NEW DNN training Dataset. simple UI . Total Project is 250 USD STAGE 1 - 100 USD STAGE 2 100 USD Deplyment, Testing and Document 50 USD STAGE 1 handles intelligence + cloud STAGE 2 handles device + communication + app STAGE- I Backend Engineer (Cloud + Data + API) Deep Neural Networks for classification (imbalanced datasets, SMOTE preferred) Python (TensorFlow/PyTorch) and model deployment via REST API Handling weather/time-series datasets Cloud hosting (Azure/AWS) and database management SMS gateway integration and push notification backend Secure API development and logging system Deliverable: Deployed ML model with working API endpoint and backend system. STAGE 2 &...

I need a concise Python 3 script that will run on a Raspberry Pi 5 and do the following: • Watch a single GPIO input line for the HIGH digital signal coming from my Sony camera’s built-in AI output. • As soon as that digital signal is detected, drive a separate GPIO output that energises a small 5 V solenoid for five seconds, then automatically switch it off. • Debounce or otherwise ignore any further triggers until the five-second period is complete. The camera only provides a digital signal, so no protocol parsing is required—plain HIGH/LOW logic on the GPIO pin is all I need. The trigger itself must use the Pi’s native GPIO header rather than USB or networking. I haven’t fixed the exact GPIO numbers yet; feel free to suggest sensible default...

The embedded system comprises 2 STM32 boards connected to their own 7 sensors, 1 motor, and 3 relays. Each is connected to a central Raspberry Pi 4 board. The RIGHT STM32 board also has a TFT ST7789 2inch display. The Raspberry Pi has its own 5-inch display (connected via HDMI) and is connected to a battery BMS via UART and controls the main ON/OFF switching of the exoskeleton system driven via a 48V 10A relay. The Raspberry Pi also controls the operation of a 5V air-pump via a relay able to deliver 1.5A. 1. Graphical user interface (GUI) developed for the STM32 to drive the ST7789 display. The detailed requirements for this GUI are presented in Figure 3. 2. GUI developed for the Raspberry Pi display. The detailed requirements for this GUI are the same as for STM32. 3. Software for...

# Embedded Linux System – Technical Specification ## Custom Hardware Platform based on Raspberry Pi CM4 --- ## 1. Project Overview This project is based on an **existing, functional custom hardware platform** using a **Raspberry Pi Compute Module 4 (CM4)**. A standard Raspberry Pi OS is already running on the device. The goal of this project is **not to create a prototype**, but to bring an **existing custom CM4-based hardware platform into a professionally engineered, maintainable, and reproducible software state**, suitable for industrial deployment and scaling. --- ## 2. Project Goals The primary project objective is to **bring a custom hardware platform with a Raspberry Pi CM4 module into a robust, industrial-grade software state**, including: - a clean and well-docu...

I’m building a smart irrigation setup that links a Raspberry Pi edge server with several ESP32 nodes in the field. Each ESP32 gathers data from soil-moisture probes, compact weather boards (temperature, humidity, barometric pressure), and inline flow meters, then reports everything wirelessly to the Pi for processing. Here’s what I need from you: • Python (Raspberry Pi) and MicroPython/C++ (ESP32) code that ingests the raw sensor streams, pushes them through an on-device model, and decides—within seconds—whether to start or stop the main pump and which solenoid valves to open. • An ML pipeline: training notebooks, a lightweight model (TensorFlow Lite or similar) and the inference wrapper that runs locally. The model must act on current soil-moisture rea...

I need help building a working prototype of a small interactive toy. The prototype requires: A pop-up mechanism (using solenoids, springs, and/or small motors). Integration with Raspberry Pi or Arduino for control. Wiring/programming to operate the mechanism. A simple phone/web app to trigger the toy remotely. Requirements: Experience with mechanical design and prototyping. Hands-on skills with Raspberry Pi/Arduino electronics. Must show past project work (photos, CAD, or GitHub). Signed NDA. Deliverable: A working physical prototype (not just design files) that demonstrates the pop-up mechanism controlled by Raspberry Pi/Arduino. Budget: Budget will be discussed based on scope and experience. Please provide: What’s your estimated cost? How did you arrive at that numbe...

I’m putting together a new Raspberry Pi build that will run Ubuntu rather than the standard Raspberry Pi OS. My own experience level is advanced, but I’d like another seasoned set of eyes to speed things up and help polish the system. The job focuses on: • Reviewing my current headless Ubuntu image for best-practice partitioning, bootloader tweaks, and basic hardening • Tracking down and fixing the boot-time warnings that surface in dmesg and journalctl • Suggesting and, where sensible, applying performance optimisations—overclock settings, thermal management, swap behaviour, I/O tweaks • Writing or refining a few clean Bash/Python scripts for unattended updates and off-device backups We’ll work entirely over SSH, so no hardware shipping...