ESP32-CAM IoT Control System

@AwaisChaudhry

Hello, I’m Muhammad Awais and I’ll craft a complete ESP32-CAM IoT setup tailored to your goals: stable low-latency video streaming, on-device or edge-friendly face recognition, and scalable light control via relays and 74HC595s. I’ll design a robust firmware flow: reliable video capture and streaming with minimal latency, a lightweight face-recognition path within ESP32 limits or an efficient edge/cloud option, and a clean driver stack for multi-channel lighting. The Android app will auto-discover the ESP32 on the local network, show live video, display face-recognition feedback, and allow per-channel or group control. All code will be well-structured, documented, and stored in a Git repository with clear flashing, wiring, and build/run instructions. The solution will use open-source components and be ready for rapid iteration with your feedback. What is your preferred face-recognition approach: on-device with the ESP32-CAM as the primary path, or a lightweight edge/cloud workflow if the ESP32 limits are exceeded? How many relay channels and shift-registers do you plan to support initially, and what is the maximum expansion you anticipate? Do you require encrypted local control and secure OTA firmware updates from the Android app? Is there a preferred Android development route (native Java/Kotlin vs. cross-platform) for the app’s performance and UX? Best regards,

@AITSoft

Hello, I understand you need a complete IoT system using ESP32-CAM that includes real-time video streaming, face recognition, and multi-channel light control with an Android app interface. I will set up the ESP32-CAM for a stable, low-latency video stream and implement efficient face recognition that fits the ESP32’s limits, either on-device or via a smart edge/cloud approach. Using shift registers like 74HC595, I’ll extend the GPIO to control multiple relays for your lights. The Android app will be user-friendly, capable of discovering the device, showing live video, face-recognition results, and toggling lights individually or in groups. The code will be clean, well-commented, and delivered in a Git repo with instructions for setup and use. Libraries will be all open-source or free for commercial use. I am ready to work closely with you for quick feedback and smooth testing. Do you prefer the face recognition processing to happen mostly on the ESP32 device itself or using a cloud/edge server for better accuracy? What is the maximum number of light channels you expect to control with the shift registers? Do you have a preferred toolkit or language for the Android app (native Java/Kotlin or cross-platform)? Will the ESP32-CAM and Android device always be on the same local network for discovery and control? Do you already have hardware components like relay modules and shift registers, or should I suggest suitable models? Thanks,

@Srashtasoft

Hi there, I have read your project requirement. You need a complete ESP32-CAM based IoT solution with real-time video streaming, efficient face recognition, scalable multi-channel light control using relay modules and 74HC595, and a user-friendly Android app for monitoring and control. We will develop a stable low-latency video streaming system, implement optimized face recognition (on-device with optional edge support), design scalable relay control architecture using shift registers, and build a smooth Android app with live feed, device discovery, and individual/group light control. The solution will include clean, well-documented code, Git repository, and complete setup instructions. Questions: ========= Do you prefer offline-only functionality or should we include remote/cloud access? How many light channels do you want to control initially and in future? Should face recognition be fully on-device or hybrid (device + server)? Do you prefer Android app in Kotlin or Flutter? Best Regards, Srashtasoft Team

@Herculesz

Hi I can build a complete ESP32-CAM IoT system with live video, face recognition, multi-channel light control, and an Android app that ties everything together cleanly. The main challenge here is balancing ESP32 hardware limits with smooth streaming, reliable recognition, and scalable output control, so I would solve that with a lightweight architecture: ESP32-CAM for capture/control, 74HC595-based output expansion, and either efficient edge recognition or a hybrid recognition flow depending on your latency target. My approach would include stable ESP32-CAM firmware, relay and shift-register control logic, local network device discovery, grouped/individual light switching, and an Android app that shows the live feed, recognition status, and control panel in one interface. I would keep the code modular, documented, and practical to flash, wire, and maintain, with clear instructions for firmware upload, relay/74HC595 wiring, and app setup. I have experience with embedded systems, mobile app integration, real-time device control, and building end-to-end IoT workflows where reliability matters more than overengineering. And I can help you so on by delivering a working, testable system you can extend later with more channels or automations. Thanks, Hercules

@engrusmanfaiz

I will develop a complete ESP32-CAM based IoT system with stable real-time video streaming and optimized face recognition using an efficient edge/cloud hybrid approach. The firmware will include structured modules for camera streaming, GPIO expansion via 74HC595, and reliable multi-channel relay control. I will design a scalable output architecture so you can control many lights beyond native GPIO limits. An Android app (Kotlin) will be built with device auto-discovery, live video view, face recognition feedback, and intuitive control interface. Communication will be lightweight (HTTP/WebSocket) to ensure low latency and stability. All code will be clean, modular, and delivered via Git with proper documentation. You will receive complete wiring diagrams and step-by-step flashing/setup instructions. Only open-source, commercially free libraries will be used. I will support testing and quick iterations until the system runs smoothly on your hardware.

@rbtech1984

Hello There!!! ★★★★ (ESP32-CAM IoT system with real-time streaming, face recognition & Android control app) ★★★★ Project understanding: I understand you need a complete IoT system using ESP32-CAM with stable video streaming, face recognition, and multi-channel relay control managed through an Android app. The system must be scalable using shift registers and include clear hardware + software integration. ⚜ ESP32-CAM firmware for stable low-latency video streaming ⚜ On-device/edge face recognition integration optimized for ESP32 limits ⚜ Relay + 74HC595 shift register based multi-channel light control ⚜ Android app (Java/Kotlin or Flutter) with live video feed ⚜ Local network device discovery & control interface ⚜ Real-time UI feedback for face recognition & device status ⚜ Full Git repo with clean, well-commented code + setup guide I have experience in IoT systems, ESP32 firmware development, Android apps, and embedded integrations with real-time streaming and hardware control. Approach: I will first stabilize ESP32-CAM streaming, then integrate lightweight face recognition (edge/cloud hybrid if needed), expand GPIO via shift registers, and build a smooth Android control app with LAN discovery and real-time updates. Let’s connect and discuss your hardware setup so we can start building the full system. Warm Regards, Farhin B.

@hayteekeys

HI, KINDLY READ THROUGH MY PROPOSAL I am Experienced ESP32-CAM IoT developer ready to deliver a complete, stable system with real-time video streaming, face recognition, multi-relay light control via 74HC595, and a smooth Android app. MY APPROACH ✅ ESP32-CAM firmware (Arduino/ESP-IDF) with MJPEG/WebRTC low-latency streaming + ESP-WHO library for on-device face detection/recognition ✅ 74HC595 shift register chain for scalable relay outputs (8+ channels) with clean GPIO expansion and debounce ✅ Android app (Kotlin) with mDNS discovery, live video feed, face feedback overlay, and individual/group light toggles ✅ Well-structured, fully commented code in a private Git repo with flashing/wiring/app build instructions RELEVANT PROJECTS - ESP32-CAM home automation system with live streaming, face detection, 74HC595 multi-relay control and native Android app DELIVERABLES - Complete ESP32-CAM firmware - Android app source + APK - Wiring diagrams, BOM and step-by-step setup guide - Git repository with all code and documentation QUESTIONS 1. Target number of light channels/relays? 2. Preferred streaming method (MJPEG or WebRTC)? 3. On-device face recognition sufficient or edge/cloud hybrid preferred? 4. When can you share hardware details for testing? Ready to start immediately.

@tshibsamuel477

Hi there, I carefully read your project description, and it strongly matches my experience in ESP32 systems, embedded control, and full hardware-software integration. I can help you build a complete end-to-end solution around the ESP32-CAM, including stable video streaming, face recognition workflow, relay and 74HC595-based light control, and a clean Android app for monitoring and control. I’m Samuel Tshibangu, a mechatronics engineer with several years of hands-on experience in embedded systems, ESP32 development, PCB design, wireless communication, and control interfaces. I’ve already worked with the types of components and architectures involved in your project, including ESP32-based devices, relay control, shift registers, sensor/IO expansion, and mobile-connected embedded systems. Because of that, I can move quickly and deliver a practical, well-structured solution. My approach is to keep the system reliable, scalable, and easy to maintain: clean firmware architecture, responsive app behavior, open-source compatible tools, and clear documentation for flashing, wiring, and testing. I can also help choose the most realistic face-recognition path for ESP32-CAM performance, whether on-device or through an efficient edge/cloud workflow. I’m confident I can deliver this efficiently and professionally. Feel free to send me a message so we can discuss the details and get started. Best regards, Samuel Tshibangu

@mobiwebsolutions

✋ Hi There!!! ✋ The Goal of the project:- Build a complete ESP32 CAM based IoT system with real time video streaming, face recognition, and scalable multi channel light control integrated with an Android app. I carefully read your requirements and understand you need an end to end embedded and mobile solution combining ESP32 CAM firmware, relay control, face recognition, and a smooth Android interface for real time control. I am the right fit because I specialize in IoT systems that combine embedded hardware with mobile applications and efficient networking. * Configure ESP32 CAM for stable low latency video streaming with optimized performance * Implement face recognition workflow using edge or cloud approach suitable for ESP32 limits * Develop Android app for live stream viewing, device discovery, and multi channel light control I will also provide UI design for the app, structured firmware code, full testing, wiring documentation, and complete source code delivery. With 9+ years experience as a full stack developer, I have worked on similar IoT and embedded control systems with mobile integration. Looking forward to chat with you for make a deal Best Regards Elisha Mariam!

@mughiraaa

Hi! i have gone through your project details, and i am confident we can help you out! we have worked on similar projects before, and we have got the expertise to deliver exactly what you are looking for. how about we set up a quick meeting to chat through everything? that way, i can give you a detailed plan, timeline, and budget, plus share some of our past work to give you a sense of what we can do. let me know a time that works for you! looking forward, Mughiraa

@MQamar123

With my extensive experience in software development and a strong background in various programming languages, I am confident that I can deliver the comprehensive, customized solution your project requires. My understanding of IoT systems, mastery of C programming and Java expertise not only aligns perfectly with the skills specified for this project but also makes me well-positioned to tackle any challenges we may encounter during implementation. Furthermore, my proficiency in mobile app development coupled with my ability to create intuitive user interfaces make me the ideal candidate for your Android app design. Whether it's native (Java/Kotlin) or using a cross-platform toolkit, my priority is ensuring a smooth user experience, while also adhering to ESP32 performance limits

@shadabkhan92

As a full stack engineering team, we are excited to apply our diverse set of skills to your ESP32-CAM IoT Control System project. The combination of our expertise in artificial intelligence, enterprise ERP systems, and hardware development aligns perfectly with your core goals for real-time video streaming, advanced face recognition, and multi-channel light control. Having developed numerous IoT solutions reliant on technologies similar to the ESP32-CAM, we are well-versed in configuring stable and low-latency video streams that cater to personalized requirements like yours. Our robust background regarding efficient edge/cloud workflows will ensure optimal integration of advanced face recognition within ESP32 performance boundaries. We can further address your need for additional controllable outputs by seamlessly incorporating 74HC595 shift registers without causing scalability issues. Furthermore, our proficiency in mobile app development makes us an ideal choice for building an intuitive Android app that will enable you to manage your entire system right from your phone. Whether it's about discovering the ESP32 on the local network or toggling each light channel individually or all together, our UI/UX skills will ensure utmost convenience. Rest assured, we do all our work transparently - well-structured, thoroughly commented code meticulously organized in a Git repository w

@hayat38402

Hi, how are you doing? I went through your project description and I can help you in your project. your project requirements perfectly match my expertise. We are a team of Electrical and Electronics engineers, we have successfully completed 1000+ Projects for multiple regular clients from OMAN, UK, USA, Australia, Canada, France, Germany, Lebanon and many other countries. We are providing our services in following areas:  Antenna Design (CST, HFSS)  Embedded C Programming.  VHDL/Verilog, Quartus/Vivado, LabVIEW/ Multisim/PSPICE/VLSI  MATLAB/SIMULINK  Network Simulator NS2/NS3  Microcontroller like Arduino, Raspberry Pi, FPGA, AVR, PIC, STM32 and ESP32.  IDEs like Keil MDK V5, ATmel studio and MPLab XC8.  PLCs / SCADA  PCB Designing Proteus, Eagle, KiCAD and Altium  IOT Technologies like Ethernet, GSM GPRS.  HTTP Restful APIs connection for IOT Communications. Also, we have good command over report writing, I can show you many samples of our previous reports. Kindly consider us for your project and text me so that we can further discuss specifically about your project's main goals and requirements.

@abdf2010

Hey, your project, ESP32-CAM IoT Control System looks like a great fit for my skills. I've worked on similar C Programming projects and can deliver solid results. Let me know if you'd like to chat about the approach.

@Nada100200

I can build a complete, production-ready IoT solution around your ESP32-CAM that delivers low-latency live video streaming, reliable face recognition, and scalable multi-channel light control with an intuitive Android app. I’ll configure the ESP32-CAM using optimized firmware (ESP-IDF/Arduino) for stable MJPEG/RTSP streaming, and implement efficient face recognition using on-device capabilities (ESP-WHO) with optional edge/cloud offloading (e.g., lightweight API with OpenCV/TensorFlow Lite) to balance accuracy and performance. For lighting, I’ll design a modular control layer using relay drivers expanded via 74HC595 shift registers, enabling dozens of channels with minimal GPIO usage, all exposed through a clean REST/WebSocket API. The Android app (Kotlin or Flutter) will auto-discover the device on the local network, display the live stream, show recognition events, and provide responsive individual/group light controls with real-time sync. The deliverables will include a well-structured Git repository with fully commented firmware, backend (if used), and mobile app code, along with clear wiring diagrams, flashing steps, and setup instructions. All tools and libraries will be open-source and commercially safe, and I’ll work iteratively with you for testing and refinements until the system runs smoothly end-to-end on your hardware

@jakubf41

I’ve worked extensively with ESP32-based systems and can build your project as a tightly integrated, real-time IoT solution rather than a collection of loosely connected features. For the ESP32-CAM, I will implement a stable MJPEG streaming server with frame rate and resolution tuning to keep latency low and avoid memory fragmentation (a common issue on this board). I’ll also include watchdog recovery and proper PSRAM usage to ensure long-term stability. On-device (ESP-WHO) for fast, offline recognition with enrolled faces stored locally Hybrid mode where frames are selectively sent to a lightweight edge service (e.g., local server/Raspberry Pi) for higher accuracy, then results are pushed back in real time via WebSocket For light control, I will design a scalable output system: Direct GPIO control for critical relays Cascaded 74HC595 shift registers driven via SPI for expansion (8, 16, 32+ channels) Latching logic to maintain states and prevent flicker on reboot Grouping support (rooms/scenes) handled both firmware-side and app-side The Android app (Kotlin) will include: mDNS-based auto-discovery of the ESP32 on your network Smooth MJPEG stream rendering (optimized to avoid UI blocking) Real-time face detection feedback (event-based, not polling) Dynamic UI that adapts to number of channels (based on device config) I can start immediately and deliver a working MVP quickly, then iterate based on your testing feedback.

@engruhulajom

Hello dear Client, I am an experienced full-stack developer with over 10 years of expertise in IoT systems, web and mobile applications, delivering scalable, real-time solutions using ESP32, Android, and cloud/edge technologies for complex hardware-software integration projects. I understand you need a complete ESP32-CAM solution with stable low-latency video streaming, efficient face recognition (on-device or edge/cloud), multi-channel relay control for lights, GPIO expansion using 74HC595 shift registers, and an Android app for device discovery, live streaming, face feedback, and individual/group light control. My skills include ESP32 firmware, C/C++, Kotlin/Java, React Native, REST APIs, IoT integration, and embedded systems. Feel free to share more details. I am ready to start and iterate quickly for best results. Best regards Md Ruhul

@cesur135

With over a decade of rich experience in designing and implementing complex automation systems, specializing in industrial projects, I believe I'm an ideal candidate to execute your ESP32-CAM IoT Control System. Having honed my skills with a wide range of PLCs and SCADA systems, I can confidently work with the ESP32-CAM board to ensure low-latency video streaming and efficient face recognition at its optimum performance levels. My expertise also extends to scaling systems beyond their native capabilities by integrating external modules like the 74HC595 shift registers - essential for expanding the GPIO count here. Moreover, as you value code quality and documentation, my technical precision in well-structured, thoroughly commented code will suit your need for a comprehensive Git repository. Though my proficiencies primarily lie in C Programming and Embedded Systems, my Java skills seamlessly combine with advanced system designing, allowing me to build an intuitive Android app that'll cater to all your needs – from live video feed and face-recognition feedback display to individual or group light control. With me, you get not just the technical prowess but also the empathy for user experience which is crucial for seamless mobile-app functionality.

@alirashdi26

Hey , I just finished reading the job description and I see you are looking for someone experienced in Java, Video Streaming, Embedded Systems, Android, Mobile App Development, Face Recognition and C Programming. This is something I can do. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: 1. These are all the requirements? If not, Please share more detailed requirements. 2. Do you currently have anything done for the job or it has to be done from scratch? 3. What is the timeline to get this done? Why Choose Me? Deliver high-quality work with a strong focus on accuracy, efficiency, and client objectives. Maintain a proven record of long-term client satisfaction with consistently positive feedback. Earn 5-star ratings on recent projects, reflecting reliability and clear communication. Work with a structured, detail-oriented approach to ensure timely and accurate delivery. Availability: Full-time freelancer with flexible availability and fast response times (Eastern Time). I will share with you my recent work in the private chat due to privacy concerns! Please start the chat to discuss it further. Regards, Ali