Mobile Development with Fexingo: iOS, Android, and App Building Conversations

In episode 104 of Mobile Development with Fexingo, Lucas and Luna explore how mobile apps are using on-device AI for real-time dance pose analysis. They break down the technology behind apps like DanceFit that can track a user's body movements and compare them to a professional dancer's, providing immediate feedback on timing, posture, and technique—all without sending video data to the cloud. The...

In this episode of Mobile Development with Fexingo, hosts Lucas and Luna explore how on-device AI is enabling real-time guitar chord detection in mobile apps. They dive into the technical challenge of identifying chords from raw audio using small neural networks like convolutional neural networks (CNNs) and CRNNs, optimized to run on phones without a cloud round-trip. With demo apps like Chord AI...

In this episode of Mobile Development with Fexingo, Lucas and Luna explore how on-device AI is transforming wine apps. They focus on the specific case of Vivino, which uses a neural network to identify wine labels from a photo and instantly returns tasting notes, ratings, and price comparisons. The hosts discuss the technical stack: a lightweight convolutional neural network trained on over 10 mil...

Lucas and Luna explore how on-device AI is enabling real-time sign language translation on smartphones. They dive into the technical challenges of capturing hand shapes, movement, and facial expressions simultaneously using the phone's camera and a lightweight neural network running entirely on the device. The episode focuses on a specific case: a 2025 research paper from Carnegie Mellon that achi...

In this milestone 100th episode, Lucas and Luna dive into a controversial but real use of on-device AI: password cracking. They explore how apps like HashCat and John the Ripper leverage local neural networks to brute-force or guess passwords billions of times per second, all on a smartphone. The discussion centers on a 2025 study from Georgia Tech showing that a flagship Android phone can crack a...

In this episode of Mobile Development with Fexingo, Lucas and Luna explore how on-device AI is transforming handwriting recognition on smartphones, moving beyond basic OCR to real-time, stroke-level analysis. They focus on a specific case: the MyScript Nebo app for iPad and iPhone, which uses neural networks to convert handwritten notes into digital text instantly, without sending data to the clou...

In this episode, Lucas and Luna explore how mobile apps use on-device AI to track trampoline jumps and flips in real time. They break down the specific sensors involved—accelerometer, gyroscope, and magnetometer—and how machine learning models classify movement patterns like continuous vertical oscillation versus a controlled flip. Lucas shares data from a study showing that jump-counting accuracy...

Smartphones today can spot a sick tomato plant before your eyes do. In this episode, Lucas and Luna explore how on-device AI is being deployed for real-time plant disease detection — from cassava in East Africa to vineyards in California. They break down the technical challenge: training lightweight convolutional neural networks on leaf image datasets, achieving 95% accuracy in under 200 milliseco...

In this episode of Mobile Development with Fexingo, Lucas and Luna dive into the fascinating world of on-device AI for lip-reading. They explore how modern smartphones can transcribe speech from silent video by analyzing mouth movements, using lightweight neural networks like LipNet. The hosts discuss the technical challenges of training on datasets like GRID and LRW, the privacy advantages of pro...

Episode 95 of Mobile Development with Fexingo dives into acoustic scene classification — on-device AI that identifies whether you're in a park, a subway, or a busy restaurant by analyzing ambient sound. Lucas and Luna break down how Google's Sound Events detection model (part of ML Kit) processes audio in milliseconds without sending data to the cloud. They explore a real-world case: a hearing aid...

Lucas and Luna explore how on-device AI is enabling real-time lip reading on smartphones. They discuss the core technology—visual speech recognition using lightweight neural networks—and highlight a real-world case: Google's Project Euphonia spin-off that helps people with speech impairments communicate via silent mouthing. The episode covers the technical challenges like lighting and angle robust...

Episode 93 of Mobile Development with Fexingo explores how on-device AI is turning smartphones into driver drowsiness detectors. Lucas and Luna break down the specific sensors and models involved: the forward-facing camera, infrared flood illuminator, and a lightweight convolutional neural network that tracks eye aspect ratio and head pose in real time. They discuss the technical challenge of runn...

In this episode of Mobile Development with Fexingo, Lucas and Luna dive into on-device depth estimation — how modern smartphones use AI to understand 3D space without cloud servers. They focus on Apple's LiDAR scanner and Google's Depth API, explaining how these technologies power features like portrait mode, AR measurement apps, and real-time object occlusion. Lucas breaks down the difference bet...

Episode 91 of Mobile Development with Fexingo dives into on-device AI for real-time skin tone matching in mobile apps. Lucas and Luna explore how companies like L'Oréal and Google have integrated inclusive skin tone sensors into smartphone cameras, enabling accurate foundation shade matching and personalized beauty recommendations without sending data to the cloud. They discuss the technical chall...

In this episode, Lucas and Luna dive into the world of computational photography on smartphones, specifically focusing on how on-device AI is now capable of removing lens flares in real time. They explore the technical challenges of distinguishing flares from legitimate light sources, the hardware accelerators like Apple's Neural Engine and Google's Tensor Processing Unit that make this possible,...

On-device AI is now being used to detect deepfakes and manipulated videos in real time, directly on your phone. In episode 89 of Mobile Development with Fexingo, Lucas and Luna explore how Intel's FakeCatcher technology and similar models analyze subtle cues like blood flow patterns in facial pixels to distinguish real from fake. They discuss the technical challenges of running these models on mob...

In this episode of Mobile Development with Fexingo, Lucas and Luna explore how on-device AI is being used to predict heart attacks in real time. They dive into a specific case: a 2025 study where a smartphone app analyzed pulse-wave data from the camera and accelerometer to flag atrial fibrillation and early signs of myocardial infarction. Lucas explains the technical pipeline — from photoplethysm...

Episode 87 of Mobile Development with Fexingo explores how modern smartphones use on-device AI to estimate calories from a photo of your meal. Lucas and Luna break down the technical pipeline: from food segmentation and classification to volume estimation and nutritional lookup. They examine the trade-offs between accuracy and speed, discuss how apps like Calorie Mama and SnapCalorie achieve sub-s...

Episode 86 of Mobile Development with Fexingo explores how modern smartphones can detect stress in real time using on-device AI. Lucas and Luna break down the biometric signals that apps analyze—heart rate variability, galvanic skin response, voice tone, and typing patterns—without sending data to the cloud. They discuss the technical stack behind apps like Mindstrong and Welltory, the challenge o...

Episode 85 of Mobile Development with Fexingo dives into real-time fashion try-on, a rapidly growing feature in shopping apps. Lucas and Luna break down how on-device AI enables users to 'try on' clothes virtually using just a smartphone camera, without sending video data to the cloud. They explore the underlying tech: human pose estimation, garment warping, and segmentation models running locally...

In this episode, Lucas and Luna explore how on-device AI enables real-time object counting in mobile apps, from counting people in retail spaces to tracking inventory in warehouses. They focus on a specific case: a grocery delivery app that uses Apple's Vision framework to count produce items in a customer's photo, reducing checkout steps. The discussion covers the underlying technology, including...

In episode 83 of Mobile Development with Fexingo, Lucas and Luna unpack how on-device AI models are being trained to detect emotion from voice in real time. They focus on a specific case: a mental health journaling app called MoodWave that uses a tiny 2.8MB model to classify seven emotional states from a few seconds of speech. Lucas explains the technical trade-offs — why the developers chose mel-...

In this episode of Mobile Development with Fexingo, Lucas and Luna explore how mobile apps now use on-device AI for real-time emotion detection. They focus on a specific use case: a mental health app called MoodMirror that analyzes facial micro-expressions to infer emotional states like stress or anxiety, all processed locally on the phone. The hosts discuss the technical stack—TensorFlow Lite run...

In this episode of Mobile Development with Fexingo, Lucas and Luna dive into the emerging field of on-device gait analysis — how smartphones use AI to analyze walking patterns from a phone's accelerometer and camera in real time. They explore a concrete case: a new health app called SteadyStep, which uses on-device neural networks to detect early signs of Parkinson's disease and fall risk, without...

In this episode of Mobile Development with Fexingo, Lucas and Luna dive into how modern mobile apps use on-device AI to detect sleep apnea in real time. They explore the Apple Watch's 2024 apnea detection feature that led to a flood of third-party apps, the technical challenge of processing blood oxygen and movement data locally on a smartphone or wearable, and the regulatory hurdles that develope...