iOS Scratch Detection App

@jastp

Greetings from Logictrix! My name is Jas, and I am looking forward to discuss about your app in details over the Chat or Call. We have enough app developers available in team so I can assure you to deliver this project at a fairly low cost with great quality and with a commitment for long term support. *** We have now earned 'Expertise' level in AI, ChatGpt and a couple of other AI platforms for App development and other Chatbot work! *** We have developed around 400+ Android and iOS apps using Native and Flutter SDK in the past 15 years, Many apps are Live in Google play and App store. We will share our detailed portfolio over the Chat once we connect. Looking forward to your reply... Thanks and Regards Jas

@AwaisChaudhry

Hello,\n\nI’m Muhammad Awais, a mobile developer focused on privacy-first iOS apps. For your iOS Scratch Detection app I propose an on-device pipeline that uses Core Motion to sample accelerometer and gyroscope data at a configurable rate (for example 20–40 Hz) with a lightweight noise filter, followed by an embedded Core ML model to spot scratching patterns. Processing will run on-device to keep data private; raw events can be exported later via a minimal backend if needed. The approach combines a small rule layer to reject obvious noise with an efficient ML model trained with Create ML and deployed as Core ML. The UI will be a single SwiftUI screen showing time-stamped events and rolling daily/weekly summaries, plus a minimal Settings view. I’ll implement unit tests and UI tests on recent iPhone models and provide a scaffold for backend export if you want it later. Milestones: 1) sampling strategy and architecture; 2) on-device detector integration; 3) UI in SwiftUI; 4) testing and battery profiling; 5) optional backend scaffold. Acceptance: aiming for at least 85% F1 on representative data, and battery impact within a few percent on current devices.\n\nWhat is your target detection accuracy (F1) and acceptable battery impact for daily use, and would you like the backend export option enabled now or later?\n\nBest regards,

@corpmember29

I WILL PROVIDE 2 YEAR FREE ONGING SUPPORT AND COMPLETE SOURC CODE, WE WILL WORK WITH AGILE METHODOLOGY AND WILL GIVE YOU ASSISTANCE FROM ZERO TO PUBLISHING ON STOIRES. I have carefully reviewed your requirements and clearly understand your vision for an iOS scratch detection app using device motion sensors. I bring 10+ years of experience in iOS development, Core ML integration, motion classification, and health/activity monitoring apps. Proposed Approach: Sensor Sampling: Core Motion framework to capture accelerometer and gyroscope data at a configurable sampling rate optimized for accuracy and battery life. Detection Logic: Hybrid approach combining simple threshold/noise filtering rules and an embedded Core ML model trained via Create ML to recognize subtle scratching patterns. Interface & Notifications: Minimalist SwiftUI interface displaying timestamped events and rolling daily/weekly summaries; push notifications triggered on configurable thresholds. Testing & Accuracy: Unit and UI tests on recent iPhone models; define acceptance criteria for detection accuracy and battery impact. Deliverables will include a fully functional app, Core ML integration, SwiftUI interface, test coverage, and documentation. Development will follow agile methodology with clear milestone-based progress. I eagerly await your positive response. Thanks

@Julian29

Hello, HAVE HANDS-ON EXPERIENCE WITH SUCH PROJECT I have 9+ years of proven experience in iOS development, on-device ML, and motion-based activity recognition, and I fully understand your requirements. The goal is to build a privacy-first, on-device iPhone app that reliably detects scratching behavior using motion sensors with minimal battery impact. Core features -->> Core Motion–based sensor sampling -->> hybrid rule + Core ML detection -->> configurable alerts & summaries -->> SwiftUI lightweight interface -->> on-device privacy. Approach: efficient sensor pipelines, Core ML / Create ML for embedded models, battery-aware sampling, clean SwiftUI architecture, and test-driven delivery. Sharing this in chat as I have a few technical questions around sampling rates, target accuracy, and background execution to proceed confidently. Thanks, Julian

@diektech

Hi, This is Elias from Miami. I have checked project description and based on the information provided, I understand that the goal of the project is to collect specific text fields from a list of websites (product descriptions, titles, meta-data, etc.) and deliver them in a clean CSV using your exact column order. If a site can’t be scraped reliably, the same fields still need to be captured manually with high accuracy, and you also want the process to be repeatable for future batches with a short handoff note + scripts. With over 10 years of experience in this field, I’m very interested because I’ve built scraping + CSV pipelines using Python (BeautifulSoup/Scrapy) and browser automation (Selenium/Playwright) and I’m used to mixing automation + manual validation when sites are inconsistent. I’d love the opportunity to discuss how I can bring this to life. Let’s connect so you can share the column format + first batch list, and I’ll confirm the best approach per site (API/RSS/html scrape/automation/manual fallback). Additionally, I have a few questions regarding your project: Q1: How many sites/URLs are in the first batch, and is it “one row per page” or “multiple items per page” (like category listings)? Q2: Do you need the exact HTML cleaned to plain text, or keep some formatting (line breaks, bullets)? Q3: Any sites behind logins, anti-bot tools, or requiring region/cookie consent steps? Looking forward to hearing from you. Regards, Elias

@JijoThomas2020

Hi, this is a well-scoped and very achievable idea. I’m a Machine Learning Engineer and AI-driven software developer with experience building privacy-first, sensor-based mobile applications using React Native, with native iOS modules for Core Motion and on-device ML. I would implement a hybrid detection pipeline where a lightweight rule layer filters obvious noise from accelerometer and gyroscope data, and a compact Core ML model handles subtle scratching patterns. Sensor data would be captured via native iOS bridges, processed fully on-device to preserve privacy, with optional event export hooks for future backend use. The app would be built with React Native for the UI, providing a clean single-screen event timeline, daily and weekly summaries, configurable thresholds, and push notifications. I focus heavily on battery efficiency, adaptive sampling, and measurable accuracy, with clear milestones covering sensor integration, model training, on-device inference, UI, and testing on recent iPhone models. I can provide a clear timeline, cost estimate, and acceptance criteria (accuracy, false positives, and battery impact) and I’m comfortable iterating quickly based on real-world data. Happy to discuss next steps and get started. Thank you, Jijo

@pinkeegupta

Hi I have read your requirements and I am sure I will be able to help you. Please message me so that we will have detail technical discussion. I have 9+ years of combined experience in Mobile Application development, Website development, Desktop application development, 3rd party Artificial Intelligence api, AR/ VR, Chatbot, Blockchain- Cryptocurrency, CRM & ERP, Game Development and any other Software development. I am having expertise in Native on Android Java, kotlin and IOS Swift, and For Hybrid Cross platform on Flutter Dart and for web and backend on react js and node js, Python Django, Power BI, Scikit-learn, Data Science AI ML, PyTorch, TensorFlow, SparkML , java spring boot and php CodeIgniter mvc. Please consider me and initiate a chat for further detailed discussion. Regards, Anju

@brayanstiven5

Hi swimtrack. I am very excited with your project because I have completed similar project recently. The skills required for your project are my main specialty. I can handle this perfectly and have abundent experiences. Please confirm that I am one of the best fits for you and drop me a message for further discussion. Thanks and Best Regards. Brayan Stiven A.

@rbtech1984

Hi There! ⚜⭐⭐⭐⭐⚜(( lightweight iphone app to detect scratching episodes using accelerometer and gyroscope sensors ))⚜⭐⭐⭐⭐⚜ I love the concept of building an on-device app that detects scratching episodes using motion sensors, with the added benefit of privacy for the user. Based on your requirements, I would recommend using Core Motion for sensor data collection and combining that with a Core ML model for detecting more subtle scratching patterns. Having worked on similar motion classification projects before, I’m confident that we can build a robust system with minimal battery impact while achieving accurate detection. I have experience in developing health monitoring apps that rely on sensor data and can share some of my relevant work in chat. Let’s connect to dive deeper into your vision and get started on this exciting project. Warm Regards, Farhin B.

@Herculesz

Hi I can build a lightweight iPhone app in Swift/SwiftUI that detects scratching from on-device accelerometer/gyroscope signals using Core Motion + a hybrid rules + Core ML pipeline. The main technical challenge is separating true scratching from look-alike motions (walking, phone handling, bed movement) without draining battery from high sampling. I’ll implement an adaptive sampling strategy (higher rate only when motion gating triggers) and a robust pre-processing layer (windowing, filtering, feature extraction). A rule-based noise filter will reject obvious non-scratch patterns, then a Core ML classifier will score candidate windows for subtle, user-specific variations. All inference will run on-device with privacy-first storage, while keeping an optional export format for future backend review/model updates. The app will log timestamped events, generate daily/weekly summaries, and trigger configurable local notifications when thresholds are exceeded. I’ll include unit tests for signal pipeline correctness and UI tests for the SwiftUI screens, plus validation tools to review false positives/negatives during iteration. Thanks, Hercules

@Mahihassi

With my profound experience in software engineering, specifically in the realm of IoT development and motion recognition, I am your ideal candidate to execute this iOS Scratch Detection App. Having completed a Master's degree in Embedded Systems, I bring a unique combination of skills to the table - including proficiency in C/C++, circuit design, firmware development, and microcontroller-based projects - which all directly connect with the core requirements of this project. My approach for sensor sampling would rely heavily on Core Motion and Core ML frameworks owing to their reliability and consistent performance. I believe that embedding a simple rule layer for filtering noise alongside a Core ML model for recognizing subtle patterns is the perfect strategy for effective scratch detection. Detail-oriented and committed to quality, I assure you of deep dedication towards meeting all your milestone deliverables while keeping an eye on battery impact. Efficiency is key for any mobile application, and I understand the tact needed to optimize performance without compromising user data security – a central concern you have expressed. Let's get started on this project, leveraging my skills in mobile app development, iOS expertise, and firm grasp on data visualization to create an app that perfectly suits your vision.

@HiraMahmood4072

Hello, With over 7 years of experience in Data Processing and Data Visualization, I have carefully reviewed your project requirements. To address the iOS Scratch Detection App project, I propose implementing a sensor sampling strategy utilizing the accelerometer and gyroscope data for motion detection. I intend to utilize Core Motion and Core ML frameworks for efficient data processing and model learning. The hybrid approach with rule-based noise filtering and machine learning models will enhance the accuracy of scratch detection. For the user interface, I plan to develop a minimalist SwiftUI design for a seamless user experience. I will focus on coding, testing, and ensuring compatibility with recent iPhone models. I have previously worked on projects involving motion classification and activity recognition, which align with the requirements of this project. I would like to discuss this project further in chat to provide more detailed insights and to understand your expectations better. You can visit my Profile: https://www.freelancer.com/u/HiraMahmood4072 Thank you.

@Fawadkaleem

The potential of your iOS Scratch Detection project has captivated my interest, and I'd love to utilize my comprehensive skills in Android and iOS development to bring your vision to life. Drawing from my years of experience, I would propose adopting Core Motion and Core ML for handling motion sensors in your app. This will maximize your users' privacy, while still allowing the possibility of a small backend for a more seamless post-processing or model updates. Backing my proposal with tangible evidence, I've successfully deployed several apps, two on iOS—IVI Cryptos and Victoria UAE Real Estate Property—administering complex tasks with efficiency while ensuring clean architecture. Recognizing this project's need for efficient motion classification and activity recognition, my previous mobile health monitoring experiences will be significant assets that put me a step ahead. Embracing Unity's 3D immersive expertise—unique among standard developers—I can further elevate the app's potential by introducing gamification elements if desired. My proficiency with AI integration complements your vision for a smart application, enabling not only data analysis and learning but also enabling automation and personalized experiences. If you trust me with this project, expect nothing less than on-time delivery, clean code selections with scalability in mind, all underpinned by an unwavering commitment to transform your idea into a powerful product. Let's proceed manfully together!

@ayesha0124

Hi there, I’m excited about your vision for the iOS Scratch Detection App! Leveraging the iPhone's accelerometer and gyroscope for precise scratching detection aligns perfectly with current trends in health monitoring and motion classification. I specialize in mobile app development and have extensive experience with Core Motion and Core ML, which will be essential for your hybrid approach to filtering noise and recognizing subtle patterns. For the sensor sampling strategy, I propose implementing a robust pipeline that collects data at optimal intervals to ensure accuracy while conserving battery life. We'll use Core Motion for real-time sensor data and employ a lightweight Core ML model, trained with relevant datasets, to enhance detection accuracy. In terms of UI, a minimalist SwiftUI interface will be implemented to provide a seamless user experience. I suggest a timeline of 30 days for coding, testing, and integration, ensuring a comprehensive yet efficient development phase. I can outline milestone deliverables like detection accuracy thresholds and battery impact metrics to facilitate swift iterations. What are your thoughts on the proposed strategy? Thanks,

@mobiwebsolutions

Hi There!!! The Goal of the project:- DEVELOP A LIGHTWEIGHT IOS APP THAT DETECTS SCRATCHING USING MOTION SENSORS WITH ON-DEVICE PROCESSING AND PRIVACY-FIRST DESIGN. I have carefully read your project description and understand you need an iPhone app leveraging accelerometer and gyroscope data, combining a rule-based filter with a Core ML model, providing push notifications and daily/weekly summaries in a minimal SwiftUI interface. I am the best fit for this project because I have extensive experience in iOS development, motion data analysis, and health/activity monitoring apps. My approach directly matches your requirements by: 1. Implementing sensor data collection using Core Motion with efficient sampling to minimize battery impact 2. Integrating Core ML for on-device scratch detection and optional backend export for post-processing 3. Designing a clean SwiftUI interface with event logs, daily/weekly summaries, and configurable notifications I provide basic services including UI design, database management, testing, and full source code delivery at project completion. I have 9+ years experience as a full stack developer and have completed multiple iOS apps involving motion classification, activity tracking, and real-time data visualization. Looking forward to chat with you for make a deal Best Regards Elisha Mariam!

@mahig47

Hello! As per your project post, you are looking to build a iOS application that detects scratching behavior using the iPhone’s built in motion sensors, with all processing handled on device for privacy. The goal is to combine a simple rule based filtering layer with a Core ML model to accurately identify scratching episodes, notify users when thresholds are exceeded, and present clear daily and weekly summaries in a minimal SwiftUI interface. My focus will be on delivering an efficient on device motion detection pipeline using Core Motion for sensor sampling and Core ML for pattern recognition, optimized for battery life and real world usage. The app will be structured to process events locally, store only essential timestamps and aggregates, and remain flexible enough to support optional backend export later without reworking the core logic. I specialize in iOS applications that rely on sensor data, on device intelligence, and privacy first design. My focus will be on clean Swift and SwiftUI architecture, reliable motion classification, and a testing strategy that validates behavior across recent iPhone models. I am comfortable documenting the sensor sampling strategy. Let’s connect to align on detection accuracy goals, background processing expectations, and the scope of v1 so we can build a focused and privacy first iOS scratching detection app. Best regards, Nikita Gupta.

@GameOfWords

iOS Scratch Detection App I’m a full-stack software engineer with expertise in React, Node.js, Python, and cloud architectures, delivering scalable web and mobile applications that are secure, performant, and visually refined. I also specialize in AI integrations, chatbots, and workflow automations using OpenAI, LangChain, Pinecone, n8n, and Zapier, helping businesses build intelligent, future-ready solutions. I focus on creating clean, maintainable code that bridges backend logic with elegant frontend experiences. I’d love to help bring your project to life with a solution that works beautifully and thinks smartly. To review my samples and achievements, please visit:https://www.freelancer.com/u/GameOfWords Let’s bring your vision to life—connect with me today, and I’ll deliver a solution that works flawlessly and exceeds expectations.

@Ahmedh058

Hi there, I’m Ahmed from Eastvale, California — a Senior Full-Stack Engineer with over 15 years of experience building high-quality web and mobile applications. After reviewing your job posting, I’m confident that my background and skill set make me an excellent fit for your project — iOS Scratch Detection App . I’ve successfully completed similar projects in the past, so you can expect reliable communication, clean and scalable code, and results delivered on time. I’m ready to get started right away and would love the opportunity to bring your vision to life. Looking forward to working with you. Best regards, Ahmed Hassan

@haseebsidd07

Hey , I just went through the project description, and I see you are looking for someone experienced in Data Visualization, Mobile App Development, iOS Development, Backend Development, Android, Objective C, iPhone, Data Processing and Mobile App Testing. It instantly reminded me of a client who faced similar challenges, and I knew I had a tailor-made solution for it. Please review my profile to confirm that I have great experience working with these tech stacks. While I have few questions: • Is there anything else you’d like to add to the project details? • What’s the top hurdle you’re facing with this project? • What is the timeline to get this done? Why Choose Me? 250+ Projects. 5 Years. Zero Misses. My reputation is built on a single metric: Flawless Execution. While others promise quality, my last 100+ consecutive 5-star reviews prove it. I don’t just finish the job; I set the standard. Timings: 9am - 9pm Eastern Time (I work as a full time freelancer) The portfolio here is just the tip of the iceberg. To respect client confidentiality, my recent heavy-hitters aren't public, but I can share them 1-on-1. Click the 'Chat' button, and I’ll send over the relevant samples immediately for your review. Regards, Abdul Haseeb Siddiqui.