Android Rewards & Minigame Bot

@corpmember29

Hello, ANDROID GAME AUTOMATION DEVELOPER {{{ I HAVE WORKED ON SIMILAR ANDROID AUTOMATION, IMAGE RECOGNITION AND GAME BOT SYSTEMS BEFORE AND I CAN SHOW YOU RELEVANT WORK. }}} I went through your requirements and understand that you need an Android bot that can detect and claim rewards, solve maze and pick-pair minigames automatically, and run continuously with activity logging. I have 11+ years of experience in Android automation, OpenCV, image recognition, TensorFlow Lite, ADB and accessibility-based automation. I can build the recognition, game-solving, automated tapping, logging and continuous-loop functionality with support for 720p and 1080p devices. I WILL PROVIDE 2 YEARS OF FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE. I am available to start quickly and can communicate promptly in English through chat or voice calls. Thanks, Christina

@sunainawbst

Android Automation | OpenCV | ADB | Image Recognition | Game Bot Hi, I can build the Android automation bot to detect reward buttons, navigate different screens, and automatically solve the maze and pick-pair minigames. I can use OpenCV/image recognition with ADB, accessibility services, or another suitable approach to achieve reliable detection across 720p and 1080p devices. The bot will run hands-free, handle continuous looping, log completed actions, and provide the APK/source code, setup instructions, image/model files, and demo video. I’m also comfortable with clear communication, quick replies when online, and short Freelancer calls when needed. Let’s connect and discuss the game flow and screens. Thanks! Purnima

@a4logic

Hello, As a seasoned developer with 15+ years of experience, I am confident I can deliver an efficient and reliable automation bot for your Android game. My extensive proficiency in Android mobile app development, Python-based AI automation, and my ability to quickly adapt to and master new tools make me an ideal candidate for this project. My skills span across numerous technologies including OpenCV, TensorFlow Lite, AutoInput, and more. I deeply understand the importance of stable and high-performing software and have a proven track record of delivering such products. Rest assured that my work will exceed your expectations with a success rate perfomance above 100% for reward elements detection across different devices and a lightning-fast solve time of less than 5 seconds for maze and pick-pair rounds. Moreover, I value open communication and commit to providing quick responses even when complex issues arise. My aim is not only to build a solid automation script for you but also to create an everlasting partnership based on trust, quality, and client satisfaction. Let's collaborate on this remarkable project to bring your vision to life! Thanks!

@ykarora26

With experience in developing automation bots, I understand your need for a robust Android game bot that excels in image recognition and gameplay efficiency. My skills in implementing image recognition algorithms and creating seamless automation processes align perfectly with your project requirements. Could you provide specific device models for compatibility testing to ensure optimal performance across various platforms? Regards, Yogesh Kumar

@dvcontact

Hello Sir, Are you ready to transform your Android game experience with an innovative automation bot tailored specifically for your needs? Our unique approach combines advanced image recognition and autonomous gameplay solutions to ensure precise and efficient performance, maximizing your rewards effortlessly. Let's discuss how this cutting-edge bot can elevate your gaming experience—I'm eager to connect and explore the possibilities! Best, Smith

@juanpablomacf

El reto aquí es lograr visión fiable en 720p/1080p y resolver minijuegos en <5 s sin que el bot parezca un macro torpe. Yo lo armaría con OpenCV para detección (plantillas normalizadas y umbrales robustos), un controlador ADB/accesibilidad con micro‑jitter humano y dos módulos rápidos: A* para laberintos y matching de características para pick‑pair. Un runner registra cada acción y mantiene ciclos largos sin fugas de memoria. Preguntas clave: • ¿Nombre del juego y si tiene anti‑bot? • ¿Prefieres emulador o dispositivo físico? Juan Pablo

@maxscender

I’ll build this as a self-contained Android bot using OpenCV for UI detection and a lightweight TensorFlow Lite model if needed for robust image recognition across 1080p and 720p screens. The reward flow will be driven by a state machine that verifies each screen before tapping, so missed buttons or unexpected popups don’t break the loop. For the minigames, I’ll implement direct pixel/screen analysis to solve mazes by pathfinding and pick-pair by memory matching, with human-like tap delays and randomized micro-movements to avoid detection. The bot will run as a foreground accessibility service, so it can operate hands-free and handle screen transitions reliably. All actions will be logged to a simple report showing rewards collected and minigames solved, with timestamps. I’ll keep the source code commented and include the image libraries and model files used, plus a short user guide and demo video. I’ll also make sure the recognition logic is resolution-aware so it meets the 100% reward detection requirement on both 720p and 1080p, and I’ll stress-test the minigame solver to stay under the 5-second average while keeping the app stable during continuous looping.

@Eliteinno

Hey, Reliable game automation depends on treating screen detection and game state as separate problems. Image matching alone can produce false taps when UI elements move between 720p and 1080p layouts, while a solver without state validation can continue from the wrong screen after a delayed animation or unexpected transition. I’d build the automation around normalized screen detection, explicit state checks, and recovery paths rather than a simple sequence of coordinates. I’d use OpenCV or an appropriate lightweight on-device recognition approach for the reward UI, with resolution-independent detection and confidence checks before actions are executed. The maze and pick-pair routines would maintain their own state, validate transitions, and log each successful or failed operation for the final report. I’d also test sustained looping on both target resolutions and handle timeouts, unexpected screens, and restart/recovery conditions so continuous execution does not depend on perfect runs. Are you able to provide the game build and representative screenshots/video captures from both 720p and 1080p devices so the recognition and minigame states can be calibrated against the actual UI?

@toriquldev123

Hello There! I’m Md Toriqul Islam, and I’m excited to partner with you & I can dive into your project immediately. I have rich experience in Python, Android automation, ADB, Appium, OpenCV, image recognition, UI testing, and automated workflow development. I have some questions: 1. Which CRM are you currently using, and do you already have the required API/integration credentials? 2. Do you have a preferred WordPress builder such as Elementor, Divi, or Gutenberg? 3. How many landing pages are you planning to build after the pilot page? I am skilled in Python, ADB, Appium, OpenCV, Android UI automation, image matching, state detection, logging, error handling, and continuous-run testing. I understand you need a hands-free Android automation bot that can reliably identify reward elements, navigate multiple game screens, solve the specified minigames, and maintain a simple activity log. I’ll focus on stability across 720p and 1080p environments, efficient recognition, crash recovery, and long-duration testing while keeping the code clearly documented and maintainable. I’m ready to start immediately and can discuss the target game screens, emulator/device setup, and required workflow. Looking forward to hearing from you. Best regards, Md Toriqul Islam

@invoketech

Hello, I have carefully reviewed your requirements and can handle the Laravel upgrade, performance optimization, bug fixing, authentication improvements, dashboard enhancements, and the upcoming Laravel–WordPress integration groundwork. I have 10+ years of experience working with Laravel/PHP applications, database-driven systems, API integrations, and existing production codebases. I will first audit the current application, upgrade Laravel safely with dependency compatibility checks, then optimize the slow areas without disturbing existing workflows. I can also keep the architecture API-ready so the future A ↔ B WordPress data synchronization can be added cleanly. WORKING FLOW: Existing Code Audit → Review Laravel version, dependencies, database structure, bugs, and current performance. Laravel Upgrade → Upgrade to the latest stable compatible release and resolve package/code compatibility issues. Performance & Bug Fixing → Identify bottlenecks, optimize queries and application flow, and resolve existing issues with before/after benchmarks. UI & Authentication → Improve authentication, dashboard, and layout while keeping existing user workflows intact. WordPress Integration Ready → Add clean APIs/hooks and document the structure needed for future two-way Laravel–WordPress synchronization. Thanks, Invoke Tech

@Tanmoy236

Hey there! I can build a hands-free Android automation bot combining OpenCV/TFLite recognition with reliable game-state handling. Here's how I'll handle it: * Detect reward UI across 720p/1080p screens * Solve maze and pick-pair rounds with optimized logic * Add continuous looping, logging and crash recovery * Deliver APK/source, models, guide + demo Our 62-person team has 9+ years’ experience. Can you share the game name and a few screen recordings/screenshots for recognition testing?

@msaqibimran

Hi, I’ve analyzed your need for an automation bot and can deliver an effective solution in about three weeks. Ensuring reliable UI detection and quick minigame solving will be my top priorities, and I’ll craft it to run autonomously with detailed reporting. Could you clarify if there are specific devices or OS versions you want to prioritize for testing? Also, how complex are the mazes and minigames? Understanding these will help in estimating the hours and finalizing the approach. For the development process, I’d use image recognition libraries to accurately identify UI elements and implement AI techniques for the minigame strategies. I’ll ensure the bot can handle variations across devices while maintaining the performance metrics you outlined. I’ve worked on similar mobile automation projects before, helping clients streamline gameplay and maximize rewards. Happy to discuss the current setup and take it from there. Best regards, Mohammad

@denisSolution

Hi, I'm Denis, a full-stack developer specializing in automation systems and mobile applications. I've built image recognition pipelines and Android automation tools, so I understand the technical challenges here. You need an Android bot that reliably identifies UI elements across resolutions, interacts accurately, and solves game logic autonomously. The core challenge is making image recognition robust for resolution variations while keeping the bot responsive during extended runs. I've built similar systems where UI detection worked consistently across multiple device configurations. My approach combines OpenCV for reliable element detection with solid state management to track progress and handle edge cases. Here's my strategy: I'll analyze game screens and build a detection model using OpenCV that identifies reward buttons and minigame elements reliably at both 1080p and 720p. Then I'll implement interaction logic through Android's accessibility service or ADB commands. For minigames, I'll code the maze solver and pick-pair logic to run at human-like speed with proper error handling. I'll add comprehensive logging for session review. The key consideration is detection accuracy across resolutions. I'll normalize screen coordinates and use adaptive OpenCV thresholds rather than hardcoding pixel values, making the bot portable across devices without recalibration. I'll build the system modularly so individual detection routines can be updated quickly if UI changes occu

@carlosd178

Hello, After reviewing your project requirements, I understand you need an Android automation solution combining image recognition, UI detection, and reliable task execution. I have experience with Android automation, OpenCV-based image processing, and building tools that interact with Android environments through ADB, emulator workflows, and accessibility-based controls. My approach would be: • Use OpenCV/image matching or lightweight vision models to detect required UI elements across different screen resolutions. • Build a reliable automation flow with screen-state checking, error handling, and logging. • Implement structured reporting so completed actions and results can be reviewed easily. • Optimize performance for long-running sessions with stability checks and recovery handling. I can provide the source code, setup instructions, recognition assets/models, and a demo showing the complete workflow. A couple of questions: • Do you plan to run this mainly on physical Android devices, emulators, or both? • Do you already have screenshots from all required game screens for building the recognition dataset? I can start immediately and will keep communication responsive throughout the project. I would first review the screen flows and recognition requirements, then provide an implementation plan and timeline. Best regards, Carlos.

@shawanay

I’m an experienced Android automation developer skilled in Java/Kotlin, OpenCV, image recognition, ADB/emulator workflows, accessibility services, and reliable UI automation. I’ll do: - Build screen-recognition logic to detect reward buttons and relevant UI states across 720p/1080p layouts, using resilient image matching rather than fixed coordinates. - Automate maze and pick-pair solving with efficient state detection, path/match logic, and configurable human-like interaction timing. - Create hands-free looping with recovery handling, screen-state validation, action logs, and a simple report showing rewards collected and rounds completed. - Deliver the Android-ready build/script, commented source, recognition assets/models, setup guide, and demo workflow, with extended stability and performance testing. I’ll keep the implementation limited to normal visible-screen interaction and supported Android automation, without bypassing game security or anti-cheat systems. Q: Can you share the game name plus sample screenshots/video of the reward screens, maze, and pick-pair minigame so I can assess UI variations before development? Regards, Shawana

@poojatdsl

I can build an Android automation bot using OpenCV/image recognition and Android automation to detect reward elements, interact with the game UI, solve the supported minigames, and run continuously with activity logging. I’ll handle multi-resolution screen detection (1080p/720p), image/template recognition, automated tapping, maze and pick-pair logic, looping/recovery handling, result logging, and continuous-run stability. The recognition layer can be structured so templates/models are easy to update if the game UI changes. The deliverables will include the Android-ready build or ADB/emulator setup, commented source code, required image/model assets, user instructions, and demonstration of the complete workflow. The implementation will prioritize reliable detection, fast decision-making, crash recovery, and clean separation between recognition, game logic, and Android automation. Ready to review the game screens/workflow and build the automation around the actual UI.

@XRProConnect

Hi, Aashiq here from Cape Town, South Africa. This project instantly caught my eye, so I had to reach out. I see you’re looking for an automation bot that can accurately detect UI elements and solve minigames quickly. The emphasis on a ≥100% success rate and the need for smooth, hands-free operation really stands out. I have extensive experience in developing automation tools and game bots that enhance user engagement and streamline processes. I’m confident I can deliver a solution that meets your criteria. Feel free to ask for samples of my previous work. Based on what you mentioned, here is how we would approach the project: - Utilize OpenCV and TensorFlow Lite for image recognition and processing. - Implement a robust logging system to track performance. - Create detailed documentation and a demo video for easy understanding. You can expect clear communication and a seamless, user-focused solution optimized for performance. Best Regards, Aashiq

@jagratip3

Hello, I have strong experience in mobile automation, Android development, image recognition, OpenCV, automation workflows, and building stable long-running applications. I can develop the bot to reliably detect reward UI elements across 720p/1080p screens, automatically solve the maze and pick-pair minigames, and operate hands-free with detailed activity logging. I’ll use the most reliable approach between OpenCV, template/feature matching, OCR, accessibility/ADB controls, or TensorFlow Lite where appropriate. The architecture will include screen-state detection, coordinate scaling, game-solving logic, retry/fallback handling, watchdogs, logging, and continuous-loop stability. Deliverables will include the Android-ready build, complete commented source, recognition assets/models, setup instructions, user guide, and demo video. I’ll specifically test against your success-rate, <5-second solving, and long-duration stability requirements. I communicate clearly, respond promptly, and am available to resolve complex issues quickly. Ready to start immediately.

@tyronet2

You need an Android automation bot that reliably recognizes reward UI, solves both minigames, and runs unattended with logging across 720p and 1080p devices. I can build this with Android automation, OpenCV image recognition, and a state-based workflow that handles screen changes, taps, retries, and continuous looping. At Marin Software, I worked on Python-based automation and real-time pipelines, including image/AI processing. I can apply that experience here to build the recognition layer, maze path-solving, pick-pair matching, reward detection, and execution/reporting flow. I’ll also structure the bot so screen coordinates are resolution-independent rather than relying only on fixed positions. I’ll provide the Android-ready build, source code, recognition assets, setup instructions, user guide, and demo. For the “100%” detection requirement, I’d validate against the supplied test devices/screens and add fallback/retry handling for missed states. Can you provide sample screenshots or a short gameplay recording of the maze, pick-pair, and reward screens?