iOS Developer with Experience in Computer Vision (YOLOv8) 2

@AwaisChaudhry

With my extensive background in both computer vision and iOS development, I am uniquely positioned to deliver on all the requirements of your project. I've not only implemented complex computer vision algorithms but also have precise understanding of working with models like YOLOv8 to deliver superior object detection and tracking functionalities. My experience with Swift and Core ML will ensure a smooth integration process that harnesses the full potential of these frameworks. Moreover, I specialize in developing efficient and reliable UIs for industrial use, which aligns perfectly with your project's objectives of traceability and performance. With real-time video processing knowledge, I can guarantee robust handling of images across different inputs - live feeds, photos or videos. My proficiency in local data persistence (Core Data, SQLite) and synchronization augments the seamless functioning of every component of your app. To further assure you of my competency - I come backed with a decade-long esteemed career that testifies my proficiency in delivering sophisticated projects with concrete results. My familiarity with large-scale data management will allow me to create comprehensive audit reports, heatmaps as well as provide efficient visual evidence storage for detailed post-analysis. Let's collaborate and leverage my skills to create an iOS application that fulfills all your technical auditing needs.

@irsolutions

As an experienced iOS developer with a strong background in computer vision projects, I understand the importance of building a native application that integrates seamlessly with YOLOv8 for object detection and tracking. Your project requires precise technical reports, heatmap generation, and a focus on reliability and performance. In past projects, I have successfully delivered similar solutions in the healthcare and FinTech sectors, showcasing my ability to implement complex functionalities while prioritizing user experience. My expertise in Core ML, real-time video processing, and data synchronization align perfectly with the requirements of your project. I am confident that my skills and experience make me the ideal candidate to bring your vision to life. Contact me today to discuss how we can start working on your iOS application that revolutionizes auditing processes. Let's create something exceptional together.

@corpmember29

I HAVE BUILT SIMILAR COMPUTER VISION APPS USING YOLO MODELS ON iOS, DELIVERING RELIABLE DETECTION, TRACKING, AND ANALYTICAL REPORTING. Core Features: Native Swift app with YOLOv8 integration (Core ML / ONNX / external API) Real-time object detection & tracking in live camera, video, or photos Audit reports with detailed logs and traceable visual evidence Heatmaps showing object presence and movement Functional, industrial-grade UI for operators and admins User Roles: Admin: full access to logs, heatmaps, and app settings Operator: limited access to live detection and reporting Deliverables: Fully working iOS app with integrated YOLOv8 Source code, setup instructions, and documentation 2 years free post-launch support I ensure high performance, modular code, and reliability for professional use. Portfolio available on request.

@Julian29

Hello, I am an iOS developer with 11+ years of experience in native Swift development and multiple computer vision integrations using YOLOv8, Core ML, ONNX, and real-time video processing. I have delivered apps for industrial audits, object detection, tracking pipelines, and automated visual reporting, which aligns directly with your project requirements. I can integrate your YOLOv8 models via Core ML conversion, ONNX Runtime, or remote inference, and implement real-time detection and tracking on photos, videos, or live camera feed using optimized pipelines for performance on iOS devices. I also have experience building heatmap overlays, detection logs, timestamped audit reports, and secure evidence storage for traceability and compliance workflows. For data persistence and audit reliability, I work with Core Data / SQLite, structured logs, and local caching, with optional sync flows. UI will be functional, stable, and optimized for operational use, with clear visualization of detections, movement paths, and generated heatmaps. I’m available to start immediately and can share portfolio samples of previous CV/ML iOS projects (object tracking, pose detection, industrial monitoring). Looking forward to contributing to your YOLOv8-based audit application. Thanks.

@ozbas

Hi — I’d like to help with your iOS computer-vision project. I’ve worked on native iOS apps involving real-time video processing, Core ML model integration, and audit/reporting workflows, so your scope fits well with my experience. I can integrate your existing YOLOv8 models using Core ML, ONNX Runtime, or an external inference API depending on performance needs. I’ve implemented object detection and multi-object tracking in live camera feeds before, including frame-by-frame analysis, bounding-box overlay, and efficient batching to maintain smooth FPS on iOS devices. Beyond model integration, I can build: • Structured audit reports with timestamps, detection metadata, and evidence files • Heatmap generation showing presence, dwell time, or movement paths • Local persistence (Core Data / SQLite) for offline logging and later sync • A stable, functional UI optimized for traceability and industrial use • Secure storage of visual evidence for post-analysis Happy to discuss the best integration approach for your YOLOv8 models.

@rbtech1984

Hello There!!! ⚜⭐⭐⭐⭐⚜(( Native iOS app integrating YOLOv8 for object detection and audit reporting ))⚜⭐⭐⭐⭐⚜ This project immediately caught my attention because it combines real-time computer vision with operational auditing, requiring both performance and reliability. You are looking for a native iOS solution that can detect and track objects, log detections, generate heatmaps, and store visual evidence for traceability. With experience in Swift development, Core ML integration, and real-time video processing on iOS, I have built apps that handle live camera feeds, object tracking, and data logging efficiently. I focus on clean architecture and reliable UI to ensure audit reports and heatmaps are accurate and actionable. Three priorities I would focus on are seamless YOLOv8 integration for detection and tracking, robust audit logging with visual evidence, and heatmap generation for movement analysis. I would be glad to discuss your model formats and UI expectations to ensure the app meets industrial auditing standards. Warm Regards, Farhin B.

@Mahihassi

Having dived into the realms of advanced computer vision applications, I bring a unique blend of skills and experiences tailored specifically for your project. Building on my Master's degree in Embedded Systems, I've successfully created applications involving object detection, tracing, and real-time video processing. My proficiency in Swift, Core ML and ONNX ensures that adopting YOLOv8 models will be a seamless process. What differentiates me is not just my technical aptitude but also my ability to understand the contextual requirements of an app. For your audit-focused app, I strongly believe in delivering functional UIs that are not just reliable and performant but also ease traceability. In addition, equipeed with experience in data logging and local data persistence like Core Data and SQLite, I'll ensure all detections are properly logged with associated video evidence stored for analysis. Lastly, it's important to note that my work doesn't end at creating functional apps; it extends to being able to effectively communicate complex analyses to non-technical stakeholders in a clear and reliable manner. Having experience with presenting results for industrial/corporate use, you can rely on me to deliver not only top-notch programming but

@mahig47

Hello As per your project post, you are looking to build a native iOS app that integrates computer vision with YOLOv8 for object detection, tracking, audit reporting, and heatmap generation. The goal is to create a reliable tool for industrial or corporate use that captures, logs, and visualizes object presence in videos, photos, or live camera feeds. My focus will be on delivering a Swift based iOS app with YOLOv8 integration through Core ML, ONNX, or external APIs, implementing accurate object tracking, audit report generation, heatmaps, and visual evidence storage. The solution will ensure real-time performance, data persistence, and clarity in reporting for post-analysis. I specialize in native iOS development, Core ML, real-time video processing, and computer vision integration with YOLO models. My focus will be on building a robust, precise, and user-friendly system suitable for industrial auditing and traceability. Let us connect to discuss your preferred model integration method, types of objects to detect, and the reporting/heatmap requirements so I can plan the architecture and workflow. Best regards Nikita Gupta

@mughiraaa

Hello, I have reviewed the details of your project. i can develop your native ios app using swift, integrating yolo v8 for object detection and tracking. the app will process live camera feeds, videos, and photos, detecting objects and logging every event. detections will generate audit reports, store visual evidence, and produce heatmaps to show object presence and movement. core ml or onnx will be used to run the models efficiently on-device. data persistence will use core data or sqlite to keep logs and synchronize results. the ui will focus on reliability and clarity, showing live detections, heatmaps, and logs in a simple, readable format. source code will be commented, and a short readme will explain setup, model integration, and data access. Let's have a detailed discussion, as it will help me give you a complete plan, including a timeline and estimated budget. I will share my portfolio in chat I look forward to hear from you. Thanks Best Regards, Mughira

@codefusion53

Hi I can build your native iOS application in Swift, integrating YOLOv8 for real-time object detection and tracking on photos, videos, or live camera feeds. The app will generate audit reports, store visual evidence, and create heatmaps based on object presence and movement, providing a reliable, traceable, and industrial-grade experience. I have experience integrating Core ML and ONNX models into iOS apps, handling real-time video processing, and implementing local persistence with Core Data or SQLite for audit logs. The UI/UX will prioritize clarity and performance, ensuring that technical staff can quickly interpret results and review evidence. I will focus on seamless model inference, accurate tracking, and robust data logging to meet your auditing requirements. Best, Justin

@shushmobiweb6

Hello!! I HAVE BUILT iOS APPS WITH YOLO & REAL-TIME COMPUTER VISION BEFORE! I’m a native iOS developer with 7+ years of experience working with Swift, Core ML, YOLO models, ONNX/TorchScript conversions, and real-time video processing. I specialize in integrating custom ML models into high-performance iOS apps for industrial auditing, tracking, and evidence capture. For your project, I will deliver a robust, audit-ready application that runs object detection and tracking smoothly across photos, videos, and live camera feed. Key Features I Will Deliver: → YOLOv8 integration via Core ML or ONNX (optimized for iOS performance) → Real-time object detection + multi-object tracking → Heatmap generation based on object presence/movement → Audit logs, timestamps, metadata, and evidence storage → Exportable technical reports (JSON/PDF) → Local data persistence (Core Data / SQLite) with optional sync → Clean, functional UI designed for operational use Technical Approach: → Model conversion + quantization for real-time FPS → AVFoundation for live camera streaming → Heatmap rendering using Core Graphics → Secure storage of visual evidence & detection history Deliverables: → Xcode project in Swift (TestFlight ready) → Complete detection/tracking pipeline → Report generation + heatmap visualization → Documentation on setup, model updates, and data flow I can start immediately and provide relevant CV/portfolio links on request. Best Regards, Sushma

@prashjain92

Hello I have carefully read your project description and I am excited about the opportunity to build a native iOS application integrating computer vision with YOLOv8. I understand the key requirements include object detection and tracking via live camera, videos, or photos, generating audit reports, creating heatmaps, and storing visual evidence for traceability. My goal is to deliver a reliable, high-performance app with a functional UI that supports industrial and operational auditing. Likely core features include YOLOv8 integration, object detection and tracking, audit report generation, heatmap visualization, and visual evidence storage. With over seven years of experience in mobile and web development, I have successfully built iOS applications with real-time video processing, Core ML integration, and robust data logging. I am confident in handling full-cycle development from model integration, UI/UX, testing, to deployment, ensuring precise and traceable results. I am enthusiastic about collaborating closely to bring your technical vision to life. Let us schedule a quick chat to align your vision and next steps. Best Regards, Prasham Jain

@draganm59

Hello Mate!Greetings Felipe P., Good evening! I am an expert mobile engineer with skills including Swift, iOS Development, Mobile App Development, Video Processing, YOLO, iPhone, Objective C, Object Detection, Computer Vision and iPad. Please send a message to discuss more regarding this project. Your Sincerely

@juanjosec63

Hello, I’m excited to work on integrating computer vision into your native iOS application using YOLOv8. With my experience in Swift and iOS development, I can seamlessly integrate YOLOv8 models via Core ML or an external API, enabling real-time object detection, tracking, and heatmap generation for audit purposes. I’ll ensure the app efficiently logs detections, stores visual evidence, and generates detailed audit reports to meet your operational and technical needs. My background in real-time video processing and data persistence will help create a reliable, high-performance UI tailored for industrial use. I’m ready to start immediately and would love to share my portfolio of computer vision projects with you. Best regards, Juan

@enervell

Hi, I'm excited about the opportunity to work on your iOS application integrating computer vision with YOLOv8. My expertise in Swift development and extensive experience with computer vision projects, particularly in object detection and tracking, position me well for this endeavor. 1. Relevant Experience: - Developed several applications utilizing YOLOv8 for real-time object recognition. - Skilled in Core ML and ONNX for efficient model integration. - Successfully implemented data logging and heatmap generation for previous projects, ensuring robust audit capabilities. 2. Proposed Approach: - Develop a native Swift application focusing on seamless integration of YOLOv8. - Ensure efficient object tracking across videos and live camera feeds. - Implement user-friendly audit reports and heatmap visualizations. I invite you to check my portfolio for similar projects, and I am eager to discuss how I can contribute to the success of your application. Thanks, Luis Cesar

@shahrukhh5

Hi! I have strong experience with iOS (Swift) and computer vision, including YOLOv8/ONNX/CoreML conversions and real-time object detection. I can integrate your models, implement precise object tracking, generate audit logs, heatmaps, and visual evidence storage exactly as required. I’ll deliver a stable, high-performance native iOS app optimized for industrial auditing and traceability. Available to start immediately — happy to share my CV/computer vision portfolio in chat. Best regards, Dev Coder Solutions

@PrateekP3003

Hi, I’m reading your project description — you need a native iOS app integrating YOLOv8 for object detection, tracking, and audit reporting. Right? I’m an expert in this field because I’ve built iOS apps using Core ML, ONNX, and live camera feeds for real-time detection and analysis. I am ready to help immediately to deliver your app with features like: Core Features: • Integration of YOLOv8 models for photos, video, and live camera feeds • Real-time object detection and tracking • Generation of audit reports with logs of all detections • Heatmap creation based on object presence and movement • Visual evidence storage for post-analysis and traceability Technical Approach: • Native Swift development for smooth performance • Core ML / ONNX model integration • Local data persistence via Core Data or SQLite • Optimized UI for industrial reliability and clarity I am a senior iOS developer with 6+ years of experience in mobile CV projects, building apps that are accurate, performant, and traceable. I can start immediately and will ensure clean, maintainable code with documentation for long-term use. Thanks & regards, Prateek

@SaadMubee

Hello, Having worked on iOS projects that blend real-time video processing with machine-learning pipelines, I can help you build a native Swift application that cleanly integrates your YOLOv8 models and delivers reliable auditing features. My approach would be to convert or load the model via Core ML or ONNX (depending on your preferred pipeline), implement efficient frame-by-frame inference, and combine that with a lightweight object-tracking module optimized for live camera feeds. Alongside detection, I’ll structure a full auditing layer — logging each event, generating heatmaps from positional data, and storing visual evidence for later traceability — all backed by a stable local persistence layer such as Core Data or SQLite. The goal is an industrial-grade UI that prioritizes clarity, performance, and trustworthiness. Before I proceed, do you want the heatmap generation to run on-device only, or should it sync to a backend for aggregated reporting? https://www.freelancer.com/u/SaadMubee Best regards, Saad Mubeen

@OneStopCr8v

Greetings Sir, Building an iOS app with YOLOv8 integration requires specialized computer vision expertise and native Swift development skills. You need a native iOS application with YOLOv8 object detection/tracking, audit reporting, heatmap generation, and evidence storage for industrial auditing purposes. What specific objects are being detected, and what is the required inference speed? This determines the model optimization approach. I have extensive experience in application development, though this project specifically requires specialized iOS computer vision and Core ML expertise which may extend beyond my core focus. View my portfolio and consistent 5-star feedback directly on my profile. https://www.freelancer.com/u/OneStopCr8v For this specialized iOS computer vision project, I'd recommend seeking a developer with direct YOLOv8 and Core ML experience, though I'm available to discuss any application architecture or UI/UX aspects. Best Regards, Jaspal