Indoor AR Mall Navigation

@toriquldev123

Dear Client, Hello There! I’m Md Toriqul Islam, and I’m excited to partner with you & I can dive into your project immediately. I’m an experienced Android developer specializing in ARCore, CameraX, OpenCV, sensor fusion, and real-time navigation systems. I understand you want an advanced AR indoor navigation system using CameraX, landmark detection, graph-based routing, sensor fusion, and real-time tracking for accurate mall navigation with AR overlays, relocalization, and continuous positioning similar to SLAM-based systems. My skills in Kotlin, ARCore, OpenCV, CameraX, sensor fusion, and pathfinding algorithms ensure robust real-time AR navigation delivery. I’m ready to start immediately and discuss architecture, timeline, and technical approach. Looking forward to your response. Best regards, Md Toriqul Islam

@jay8mac

Lets chat, a free consultation and no obligation. I understand you need a clean, professional, and user-friendly solution for your "Indoor AR Mall Navigation" project. My skills in PHP, Java, JavaScript are a perfect fit for this project. While I am new to freelancer.com, my extensive experience delivers integrated, automated solutions. Regards, Jason McLachlan

@gazmirs

Hi, ⭐15+ Yrs Sr Developer here⭐ I have experience with real-time tracking systems, AR workflows, sensor-based positioning, and performance-focused mobile development using Kotlin and modern Android frameworks. Your project requires much more than standard navigation, and I understand the challenges around indoor localization, sensor fusion, drift correction, CameraX pipelines, and AR overlay rendering. I can help structure the app with a modular architecture covering landmark detection, graph-based routing, dead reckoning, relocalization logic, and ARCore navigation flows. I’m also comfortable working with OpenCV, SQLite, coordinate transformations, and optimization for continuous real-time tracking on Android devices. My focus would be building a stable, scalable foundation first so future ML models, SLAM improvements, and advanced localization features can be added cleanly over time. If you think I am a good fit, feel free to ping me anytime. — GAZMIR

@joelm0515

Hello, I'm Joel, a senior Android developer with experience in AR, CameraX, and sensor fusion. I understand you need a production-ready AR indoor navigation app that detects landmarks, estimates user position, fuses sensor data, and provides real-time AR guidance with graph-based routing. I can build a modular Kotlin app with CameraX live preview, OpenCV-based landmark detection, PnP pose estimation, dead reckoning, and A* pathfinding for navigation. The system will include confidence scoring, drift correction, relocalization, and AR overlays for turn-by-turn guidance. I’ll deliver clean, maintainable code, documentation, and a production-ready UI optimized for performance in large indoor spaces. Best regards, Joel M.

@anilptk

Hi. I saw your project and think I can deliver what you need. Indoor AR Mall Navigation I understand the project goals and expected outcome. Want I will meet deadlines. keep you updated. and deliver high quality work. I’m offering best quality and highest performance at lowest price I am a skilled freelancer with 10years of experience in Mobile App Development, Android, Unity 3D, Unity clients and always aim for clear and steady delivery. I have completed many projects for always aim for clear and steady delivery. Hello. I am available now to assist you. Thank you for considering my proposal. Warm regards, anilptk

@vasylklymiu

Hi there I can help with this and I can start right away. I work with Kotlin ARCore and Computer Vision and I have 6 years experience building real time mobile systems where camera processing tracking and sensor data all need to stay synchronized instead of fighting each other every few seconds. For this project I would structure the app with a modular Android architecture using CameraX for live capture ARCore for spatial alignment OpenCV for landmark processing and sensor fusion layers for dead reckoning drift correction and continuous indoor positioning while keeping routing and localization separated into scalable services. I would also focus heavily on performance and recovery handling because indoor AR navigation gets messy very quickly once tracking confidence drops so relocalization logic confidence scoring and corridor constraints need to work smoothly in real time instead of just looking good in demos. Looking forward to building something genuinely advanced with you because this is much more interesting than another delivery app with floating buttons everywhere.

@solutionsplayers

As a seasoned full stack developer with over 6 years of experience, I have not only the technological proficiency but also the necessary domain knowledge for your AR Indoor Navigation Project. Although I specialize in PHP, Laravel, ReactJS, and Flutter, my expertise extends to other programming languages as well. In fact, I am no stranger to Android native development using Kotlin and have worked with the likes of CameraX and OpenCV - both of which feature prominently in your project requirements. Adapting to new technologies has always been one of my core strengths. Given this, I envision no trouble for me in grasping the essential principles of computer vision, sensor fusion, and real-time positioning needed for this complex navigation system. Further, my experience in designing cle In conclusion, I possess the pre-requisite technological acumen coupled with a diligent work ethic needed to deliver a robust backend system and an efficient frontend solution. With me on board, you can rest assured that long-term collaboration will become delightful reality rather than a distant probability. Let's connect and discuss how best to bring your vision to life while working together towards your digital goals.

@abhiramukk

Hi, This is Abhiram from UK. I understand the challenge of developing an Android AR Indoor Navigation App for malls, focusing on CameraX, Sensor Fusion, and AR features. I have experience in similar projects and comprehend the technical complexities involved. In approaching this project, I prioritize stable execution, seamless scalability, and optimal performance to ensure a user-friendly experience. The focus will be on delivering a robust system with efficient localization, navigation, and sensor fusion functionalities. Let me ask you a couple of things so I understand it better: Q1- Do you have specific requirements for the AR navigation overlays? Q2- How critical is real-time rerouting for the application? Looking forward to discussing the project details further and exploring potential collaboration opportunities.

@demivision

With my 20+ years of experience, I've honed my skills in Android native development, Computer Vision and Mobile App Development which blend seamlessly with your project requirement. My extensive experience specifically in developing and implementing AR navigation apps instills a deep understanding of the intricate demands and challenges your project necessitates. I have the unique ability to optimize the use of various tools to deliver high quality, performant solutions. My proficiency in Kotlin allows me to utilize CameraX, OpenCV and ARCore adeptly; while my expertise in Sensor fusion and Graph/pathfinding algorithms bolster the performance of navigation systems. Emphasizing on clean architecture and scalability, I assure efficient codebase that is easy to navigate and maintain in future updates. My keen eye for detail ensures the proper implementation of all core features, including Dead reckoning and Drift correction required for accurate indoor tracking. Past projects involving AI integration and mobile application development adds another feather to my cap as your project necessitates an AI-backed system for Computer Vision comparing embeddings against landmarks/logos. Finally, anticipating your query on timeline, I'd be able to deliver a production-ready implementation within X months followed by seamless transitioning to long-term support mode for any future enhancements or updates needed. In sum, you're not just hiring someone who can code; rather a seasoned professional capable of tying together your sophisticated requirements to finally present a user-friendly Android AR Indoor Navigation App tailored exclusively for malls and large indoor spaces.

@manthank44

Hello, I'd be delighted to assist with your advanced Android AR Indoor Navigation project. With extensive experience in Android development, ARCore, CameraX, and real-time tracking systems, I am well-equipped to tackle the challenges related to computer vision, indoor navigation, and sensor fusion. Understanding the complexities involved in such projects, I am familiar with the importance of performance optimization and ensuring seamless cross-functional compatibility. Here's how I'll approach your project: ✔ Implement CameraX live camera preview for landmark/logo detection ✔ Develop a robust localization pipeline with graph-based constraints ✔ Integrate sensor fusion using accelerometer, gyroscope, and compass for accurate positioning ✔ Build an AR navigation system with waypoint indicators and turn guidance ✔ Ensure clean architecture and thorough documentation ✔ Optimize performance for a seamless user experience My goal is to deliver a cutting-edge solution that exceeds your expectations and establishes a solid foundation for your indoor navigation app. Best regards, Manthan

@dmytros77

Hello Dear, I am a senior mobile app developer with extensive experience in creating advanced AR indoor navigation systems. ✔ Android native development with expertise in Kotlin ✔ Proficient with CameraX and ARCore ✔ Skilled in OpenCV and sensor fusion ✔ Experienced in real-time tracking systems ✔ In-depth knowledge of computer vision and indoor navigation ✔ Expert in graph and pathfinding algorithms ✔ Familiar with SQLite/local databases and performance optimization Previously, I developed an AR-based indoor navigation app for a tech conference, integrating real-time positioning and AR rendering for seamless user experience. I will deliver a comprehensive Android solution, complete with a clean architecture, robust localization, and a production-ready UI. Send me a message to discuss in detail. Thank you.

@mubashir021

I am excited to propose my services for your advanced Android AR Indoor Navigation project. With extensive experience in Android native development using Kotlin, CameraX, ARCore, and computer vision, I am well-equipped to create a robust indoor navigation system. My background includes developing applications that leverage sensor fusion techniques, real-time tracking, and AR rendering, making me a perfect fit for this project. I understand the complexity of integrating various components such as landmark detection, graph-based routing, and real-time navigation. My approach will ensure a clean, modular architecture that supports scalability and future updates. I have successfully completed similar projects, which you can view in my portfolio. I anticipate that delivering a production-ready application with all required features will take approximately 14 days. This timeline includes thorough planning, implementation, testing, and revisions to ensure high quality and performance optimization. I look forward to discussing your vision further and sharing my insights on technology recommendations. Let’s create an exceptional AR navigation experience together.

@aaronrobs

⭐ONLY PAY IF YOU’RE IMPRESSED⭐ With extensive experience building advanced AR indoor navigation apps, we specialize in CameraX, Sensor Fusion, and real-time localization. We can deliver a robust, modular Android solution tailored to your mall navigation needs. Core Deliverables: • Localization pipeline & AR overlays • Real-time navigation & rerouting • Sensor fusion with dead reckoning • Clean, documented codebase Approach: • Agile development with frequent demos • Performance optimization & error handling • Modular, scalable architecture • User-centric UI/UX design What’s your budget range? Once I know the budget and scope, I can provide a timeline and project breakdown. Committed to delivering quality that meets your goals. Looking forward to discussing this further. Kind regards, Aaron Roberts Happy Screen Solutions

@joevenheld

Hi, I will develop your advanced Android AR Indoor Navigation App leveraging CameraX, OpenCV, and ARCore. My strong background in computer vision and real-time tracking systems aligns perfectly with your requirements. I’ve successfully built similar applications that combine AR navigation and sensor fusion, ensuring robust indoor localization and user-friendly interfaces. My approach will include a modular architecture with a clear localization pipeline, integrating multi-landmark detection and graph-constrained localization. I will implement A* pathfinding for efficient route generation and ensure real-time tracking through robust sensor fusion techniques. My previous projects have involved performance optimization, ensuring smooth AR overlays and accurate dead reckoning. Could you share your preferred architecture style or any existing data models? Also, what is your target platform version for the app? Let’s move forward with transforming your vision into a functional, production-ready application. Thank you.

@cedric0410

Hi, I can build your Android AR indoor navigation app with a production-ready, modular Kotlin architecture. I’ll use Kotlin, CameraX, ARCore, OpenCV, TensorFlow Lite/ONNX, SQLite, and sensor APIs for real-time camera processing, AR overlays, local matching, and offline navigation state. For localization, I’ll design landmark/logo detection, embedding similarity scoring, confidence validation, image-coordinate extraction, and graph-constrained PnP pose estimation. For navigation, I’ll implement A* routing, waypoint generation, corridor constraints, rerouting, drift correction, and shared session state. For tracking, I’ll fuse accelerometer, gyroscope, compass, and step detector data using dead reckoning with relocalization triggers to reduce indoor drift. For AR, I’ll build coordinate transforms, projection logic, arrows, turn indicators, and screen-space overlays optimized for stable frame performance. I have worked on Android camera-based CV apps, ARCore overlays, sensor-driven tracking, route guidance logic, and local database-backed mobile systems. I’m confident I can deliver clean source code, documentation, error recovery, and a scalable foundation for future SLAM/ML upgrades. Please share your mall map format, landmark dataset expectations, and preferred timeline so I can propose the best technical plan. regards Cedric

@emanz03

The difficult part here is not AR rendering itself, it’s keeping localization stable once visual detection confidence drops in long corridors, crowded areas, or repeated storefront patterns. Most indoor AR demos break exactly there. I have worked on mobile CV pipelines using CameraX + OpenCV where sensor drift and relocalization became the real engineering problem, not the UI layer. Your graph-constrained approach with confidence validation is the right direction for this kind of environment. I would split this into independent modules first: landmark detection/localization, sensor fusion + dead reckoning, then AR navigation/rendering on top so rerouting and drift correction stay isolated and testable. One thing I would like to clarify early: will the mall graph, landmark positions, and store embeddings already exist, or is the app also expected to include the mapping/data collection pipeline?

@riyat950

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@rogelitoc

Hello, In my opinion, the problem of this project is that achieving accurate indoor navigation requires robust integration of AR, computer vision, and sensor fusion technologies. I will implement a clean architecture leveraging CameraX for real-time landmark detection and OpenCV for image processing, ensuring efficient data flow through a well-defined localization pipeline. The navigation system will utilize A* pathfinding, integrating sensor data for drift correction and continuous tracking. I will prioritize modularity to facilitate future updates while ensuring thorough error handling and recovery mechanisms. The deliverables will include full Android source code, a modular codebase, comprehensive documentation, and a production-ready UI, alongside the complete localization and AR navigation systems. My extensive background in Android development and AR applications ensures high-quality output. I am open to work immediately. Best Regards.

@Zesbastian

The freelancers bidding here are treating this like a basic map app. They don't realize that building a custom Visual Positioning System (VPS) with Graph-constrained PnP solvers and Dead Reckoning is an elite Computer Vision engineering task, not a UI job. As a Senior AR & Computer Vision Architect, my approach tackles the real bottlenecks of indoor mall navigation: • Drift & Magnetic Interference: Standard compasses fail inside steel-framed malls. I implement a robust Extended Kalman Filter (EKF) combining your IMU sensor fusion with ARCore's odometry to minimize dead-reckoning drift between visual relocalizations. • Optimized Visual Pipeline: Feeding CameraX frames directly into quantized TFLite/ONNX models for fast embedding extraction, matching them against a local vector database to achieve real-time PnP pose estimation without thermal throttling the CPU. • Graph-Constrained Routing: A* pathfinding strictly clamped to your navigational meshes, ensuring AR projection overlays never guide users through physical walls or closed stores. Feel free to review my profile portfolio for live, production-grade architectural systems I’ve engineered. Critical question: Malls suffer from dynamic lighting and constant store storefront changes. Are your landmark embeddings fetched dynamically via an edge-cloud sync to adapt to these changes, or are we pre-packaging a static ONNX model within the APK for purely offline matching? Sebastián Calvo | Wave Studio Design