What are OpenCV libraries. How are they used to build fitness applications

 OpenCV (Open Source Computer Vision Library) is a popular open-source computer vision and machine learning software library. It provides a comprehensive set of functions and algorithms for image and video processing, object detection and tracking, feature extraction, and more. OpenCV libraries are the collection of modules and tools that make up the OpenCV framework. Here are some key components of OpenCV libraries:

1. Core Library: The core library provides fundamental data structures and functions for handling images, matrices, and arrays. It includes operations for pixel manipulation, basic image processing tasks, linear algebra operations, and memory management.

2. Image Processing Library: This library offers a wide range of functions and algorithms for image enhancement, filtering, morphological operations, edge detection, and color space conversions. It provides tools to manipulate and analyze images, such as resizing, cropping, and histogram equalization.

3. Video Processing Library: The video processing library contains functions for video capture, decoding, encoding, and analysis. It enables developers to process video frames, extract features, perform motion detection, and track objects in video sequences.

4. Object Detection and Recognition Library: OpenCV includes libraries for object detection and recognition using techniques such as Haar cascades, HOG (Histogram of Oriented Gradients), and deep learning-based approaches like the DNN (Deep Neural Network) module. These libraries enable applications to detect and recognize objects in images or video streams.

5. Machine Learning Library: OpenCV's machine learning library provides algorithms and tools for training and using machine learning models. It includes classifiers, clustering algorithms, regression models, and tools for feature selection and dimensionality reduction.

6. GPU Acceleration Library: OpenCV provides GPU-accelerated versions of many algorithms, allowing developers to leverage the computational power of GPUs for faster image and video processing. These GPU modules utilize frameworks like CUDA and OpenCL to offload computations to the graphics hardware.

7. Integration Libraries: OpenCV can be integrated with other libraries and frameworks. For example, it supports integration with popular deep learning frameworks like TensorFlow and PyTorch, allowing developers to combine computer vision and deep learning capabilities.

OpenCV libraries are widely used in various domains, including robotics, augmented reality, medical imaging, surveillance systems, and, of course, fitness applications. They provide powerful tools and algorithms for tasks like image-based motion tracking, object recognition, pose estimation, and gesture analysis, enabling developers to build advanced and intelligent fitness applications with computer vision capabilities.

To utilize OpenCV libraries, developers need to install the OpenCV framework and include the necessary libraries in their projects. They can then access the functions and algorithms provided by OpenCV to process images, analyze videos, detect objects, and perform other computer vision tasks in their fitness applications.

How are they used to build fitness applications

OpenCV libraries can be leveraged in fitness application development to incorporate computer vision capabilities and enhance various aspects of the application. Here are some ways OpenCV libraries can be used in building fitness applications:

1. Human Pose Estimation: OpenCV provides algorithms and functions for human pose estimation, which can be utilized in fitness applications for analyzing body movements, tracking exercise form, and providing real-time feedback on posture and alignment during workouts. Pose estimation algorithms, such as OpenPose, can be integrated with OpenCV to extract joint positions and skeletal information from images or video streams.

2. Object Detection: OpenCV's object detection capabilities can be employed in fitness applications to identify and track specific objects or equipment. For example, it can be used to detect and track exercise equipment, such as dumbbells, resistance bands, or yoga mats, in video streams or images. This can facilitate automated exercise tracking, counting repetitions, or providing instructional feedback.

3. Gesture Recognition: OpenCV libraries enable developers to implement gesture recognition in fitness applications. Hand gesture recognition can be employed to control the application, switch between workout routines, or perform specific actions. OpenCV provides tools for capturing and processing video input, extracting hand features, and recognizing predefined gestures.

4. Activity Monitoring: OpenCV can be utilized for activity monitoring in fitness applications. By analyzing video streams or image sequences, OpenCV can detect and track human movement patterns, estimate step count, measure workout intensity, or monitor exercise performance metrics like range of motion or velocity. This information can be used for personalized feedback and progress tracking.

5. Real-time Video Analysis: OpenCV libraries enable real-time video analysis in fitness applications. They can be utilized to capture and process video streams from cameras or other sources, facilitating live video feedback, exercise demonstrations, or virtual trainer interactions. Real-time analysis can also help monitor user performance, detect anomalies or incorrect movements, and provide instant corrective guidance.

6. Biometric Measurements: OpenCV can be used in conjunction with other techniques, such as facial recognition or image processing, to extract biometric information in fitness applications. For example, it can be employed to analyze heart rate from video streams by measuring subtle changes in skin color caused by blood flow.

These are just a few examples of how OpenCV libraries can be applied in fitness application development. The flexibility and wide range of computer vision capabilities offered by OpenCV allow developers to integrate advanced visual analysis features into fitness applications, enabling enhanced user experiences, personalized feedback, and automated monitoring of fitness activities.

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What are Hexagon libraries. How are they used to build fitness applications

 

Hexagon libraries refer to a set of software libraries developed by Qualcomm for their Hexagon DSP (Digital Signal Processor) architecture. The Hexagon DSP is a specialized processor designed for handling digital signal processing tasks efficiently, such as audio, video, imaging, and other multimedia processing.

The Hexagon libraries provide developers with tools and APIs to leverage the capabilities of the Hexagon DSP. These libraries offer optimized functions and algorithms that can be used to accelerate computation-intensive tasks and improve performance in various domains. Here are some key Hexagon libraries:

1. Hexagon SDK: The Hexagon Software Development Kit (SDK) provides a comprehensive set of development tools, compilers, and libraries for programming Hexagon DSPs. It includes APIs, examples, and documentation to help developers utilize the Hexagon DSP's capabilities in their applications.

2. Hexagon Vector eXtensions (HVX) Libraries: HVX is an SIMD (Single Instruction, Multiple Data) architecture extension of the Hexagon DSP. HVX libraries provide optimized functions and routines for vector processing, enabling efficient parallel execution of operations on large data sets. These libraries are commonly used in multimedia and image processing applications.

3. Hexagon Performance Libraries: These libraries offer optimized algorithms and functions for common signal processing tasks. They provide accelerated implementations of operations such as fast Fourier transform (FFT), matrix operations, filtering, and other computational tasks. Hexagon Performance Libraries help developers improve the performance and efficiency of their applications running on the Hexagon DSP.

4. Hexagon Framework Libraries: These libraries provide higher-level abstractions and APIs for developing applications on the Hexagon DSP. They facilitate tasks such as task scheduling, memory management, inter-processor communication, and synchronization, simplifying the development process for Hexagon-based applications.

The Hexagon libraries are primarily used in Qualcomm's chipsets and platforms that incorporate the Hexagon DSP. They enable developers to offload specific computational tasks to the DSP, taking advantage of its specialized hardware and improving overall system performance, power efficiency, and battery life.

It's important to note that working with Hexagon libraries requires familiarity with the Hexagon DSP architecture and the associated programming model. Developers need to have knowledge of parallel programming, signal processing algorithms, and the Hexagon SDK to effectively utilize these libraries in their applications.

How are they used to build fitness applications

Hexagon libraries, developed by Qualcomm for their Hexagon DSP architecture, can be used in fitness application development to enhance performance, power efficiency, and enable specialized signal processing capabilities. Here's how Hexagon libraries can be utilized in building fitness applications:

1. Signal Processing Acceleration: Fitness applications often involve real-time signal processing tasks, such as audio processing, sensor data analysis, and motion tracking. Hexagon libraries provide optimized algorithms and functions for these tasks, allowing developers to offload computationally intensive signal processing operations to the Hexagon DSP. This offloading can improve performance and responsiveness of the fitness application while minimizing the impact on the main processor.

2. Multimedia Processing: Fitness applications may require multimedia capabilities for tasks like audio playback, video rendering, or image processing. Hexagon libraries, such as the Hexagon Vector eXtensions (HVX) libraries, enable efficient multimedia processing by leveraging the parallel processing capabilities of the Hexagon DSP. This can result in smoother video playback, faster image processing, or enhanced audio effects in fitness applications.

3. Power Efficiency: Hexagon DSP is designed to be power-efficient, making it well-suited for battery-powered fitness devices or mobile applications. By utilizing Hexagon libraries and offloading appropriate tasks to the DSP, fitness applications can reduce the workload on the main processor, leading to lower power consumption and extended battery life.

4. Performance Optimization: Hexagon libraries, including the Hexagon Performance Libraries, provide optimized functions and algorithms for common signal processing tasks. By using these libraries, fitness application developers can leverage the Hexagon DSP's specialized hardware and improve the performance and efficiency of their algorithms, such as fast Fourier transforms (FFT) for heart rate analysis or sensor fusion for motion tracking.

5. Sensor Data Processing: Fitness applications often rely on data from various sensors like accelerometers, gyroscopes, or heart rate monitors. Hexagon libraries can assist in efficiently processing and analyzing sensor data on the Hexagon DSP, leveraging its computational capabilities for real-time monitoring, data fusion, and analytics.

To utilize Hexagon libraries in fitness application development, developers need to have knowledge of the Hexagon DSP architecture, programming model, and the associated Hexagon SDK. They can utilize the provided APIs, tools, and optimized functions to leverage the power of the Hexagon DSP for specific signal processing and multimedia tasks, resulting in improved performance, power efficiency, and a better user experience in fitness applications.

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What are Open GL libraries. How are they used to build fitness applications

OpenGL (Open Graphics Library) is a cross-platform, low-level graphics programming API that enables developers to interact with graphics hardware and create 2D and 3D graphics in applications. OpenGL libraries refer to the collection of libraries and tools associated with the OpenGL API. Here are the key components of OpenGL libraries:

1. OpenGL API: This is the core programming interface that provides functions and commands for rendering 2D and 3D graphics. The API defines a set of standard functions for tasks such as creating rendering contexts, manipulating graphics objects, specifying transformations, and applying various rendering techniques.

2. OpenGL Utility Library (GLU): GLU is an auxiliary library that provides additional functionality on top of the core OpenGL API. It includes utility functions for tasks such as shape tessellation, image loading, texture mapping, and matrix manipulation.

3. OpenGL Extension Wrangler Library (GLEW): GLEW is a library that helps manage OpenGL extensions. It provides functions to query and access OpenGL extensions supported by the graphics hardware and the driver. GLEW simplifies the process of dealing with different versions of OpenGL and their extensions across different platforms.

4. OpenGL Shading Language (GLSL): GLSL is a high-level shading language that allows developers to write shaders, which are small programs executed on the graphics card to perform specific rendering tasks. GLSL is used to define the behavior of vertex shaders, fragment shaders, and other types of shaders in an OpenGL application.

5. OpenGL Mathematics (GLM): GLM is a mathematics library specifically designed for use with OpenGL. It provides a collection of mathematical functions and types commonly used in graphics programming, such as vectors, matrices, quaternions, and transformations. GLM simplifies complex mathematical calculations required for tasks like transformations, lighting, and projection in OpenGL applications.

These OpenGL libraries, along with other supporting libraries and tools, make it easier for developers to work with the OpenGL API and create graphics-intensive applications. They provide additional functionality, simplify certain tasks, and ensure cross-platform compatibility. By utilizing these libraries, developers can harness the power of graphics hardware and create visually rich and interactive applications across a wide range of platforms.

How are they used to build fitness applications

OpenGL libraries can be utilized in fitness applications to create visually appealing and interactive user interfaces, render 2D/3D graphics, and enhance the overall user experience. Here are some ways OpenGL libraries can be used in fitness application development:

1. User Interface Design: OpenGL libraries enable developers to create visually appealing and intuitive user interfaces for fitness applications. By utilizing OpenGL functions, developers can design and render interactive buttons, menus, graphs, and other UI elements to enhance the overall look and feel of the application.

2. Graphical Data Representation: Fitness applications often involve presenting data in graphical formats such as charts, graphs, and diagrams. OpenGL libraries can be used to render and animate these graphical representations, providing users with a clear visual understanding of their fitness progress, statistics, and trends.

3. 3D Visualization: For fitness applications that involve virtual environments or 3D models, OpenGL libraries enable developers to render realistic and immersive 3D scenes. This can be used, for example, to simulate outdoor running routes, visualize workout equipment, or create interactive virtual fitness trainers.

4. Real-Time Feedback and Animation: OpenGL libraries support real-time rendering and animation capabilities, allowing developers to provide immediate feedback during fitness activities. This can include visual cues, animations, and effects that respond to user input or changing workout parameters, enhancing user engagement and motivation.

5. Cross-Platform Compatibility: OpenGL is designed to be cross-platform, enabling fitness applications to run on various operating systems and hardware configurations. By using OpenGL libraries, developers can ensure that their fitness applications perform consistently across different platforms and take advantage of the available graphics capabilities.

It's important to note that working with OpenGL libraries requires proficiency in graphics programming and familiarity with the OpenGL API. Developers need to understand concepts such as rendering pipelines, shaders, and 3D transformations to effectively utilize OpenGL libraries in fitness application development.

While OpenGL provides powerful graphics capabilities, it's worth considering that newer graphics APIs like Vulkan and DirectX 12 have emerged since OpenGL's inception. These APIs offer enhanced performance and features, and developers may choose to explore these alternatives for building cutting-edge fitness applications.

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What are Vulkan runtime libraries. How are they used to build fitness applications

 

Vulkan Runtime Libraries, also known as Vulkan SDK or Vulkan API, are a set of tools and libraries provided by the Khronos Group. Vulkan is a low-level cross-platform graphics and compute API (Application Programming Interface) that allows developers to interact with graphics hardware more efficiently.

The Vulkan Runtime Libraries consist of the following components:

1. Vulkan Loader: It acts as an intermediary between an application and the Vulkan driver installed on the system. The loader manages the discovery and loading of the appropriate Vulkan driver for the graphics hardware.

2. Vulkan API: This is the core Vulkan programming interface. It provides developers with a low-level interface to access and control the capabilities of modern GPUs (Graphics Processing Units) for rendering graphics and performing general-purpose GPU computations.

3. Validation Layers: These optional components provide runtime validation and debugging features to help developers identify and resolve issues in their Vulkan applications. Validation layers can check for correct API usage, detect potential errors, and provide detailed diagnostic information.

4. Vulkan Tools: The Vulkan SDK includes various tools to aid Vulkan application development. These tools include utilities for capturing and analyzing API calls, shader compilation and validation, performance profiling, and more.

It's worth noting that the Vulkan Runtime Libraries are typically installed along with graphics drivers, especially for systems with compatible GPUs. They are not harmful or malicious software; instead, they are necessary for running Vulkan-based applications or games that utilize the Vulkan API.

How are they used to build fitness applications 

Vulkan Runtime Libraries, as low-level graphics and compute API libraries, can be used in fitness applications to leverage the capabilities of modern GPUs for rendering graphics, performing complex calculations, and enhancing visual experiences. Here's how Vulkan can be utilized in fitness application development:

1. Enhanced Graphics and Visualization: Vulkan allows developers to harness the power of GPUs to render high-quality graphics and visual effects in fitness applications. This can include realistic 3D models, immersive user interfaces, and visually appealing workout environments.

2. Accelerated Computational Tasks: GPUs excel at performing parallel computations. Fitness applications can leverage Vulkan's compute capabilities to accelerate tasks such as real-time data processing, analysis, and simulations. For example, applications that track and analyze biometric data or provide real-time feedback during workouts can benefit from Vulkan's compute capabilities.

3. Performance Optimization: Vulkan provides developers with fine-grained control over graphics rendering, allowing for optimization of resource usage, rendering pipelines, and rendering techniques. This can result in improved performance and responsiveness of fitness applications, ensuring smooth and fluid user experiences.

4. Cross-Platform Compatibility: Vulkan is designed to be cross-platform, meaning it can be used to develop fitness applications that run efficiently on different operating systems, including Windows, macOS, Linux, Android, and more. This allows for broader accessibility and reach of fitness applications across various devices and platforms.

5. Integration with Sensor Data: Fitness applications often rely on sensor data from devices like heart rate monitors, accelerometers, or motion sensors. Vulkan can be used to efficiently process and visualize sensor data, allowing for real-time updates and interactive feedback based on the collected information.

It's important to note that utilizing Vulkan in fitness application development requires expertise in graphics programming and familiarity with the Vulkan API. Developers need to have a good understanding of GPU architectures, rendering techniques, and parallel computing concepts to fully leverage the capabilities of Vulkan in their fitness applications.

While Vulkan can bring performance and visual enhancements to fitness applications, it's crucial to consider the specific needs and requirements of the application to determine whether using Vulkan is appropriate and beneficial.

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Health and Fitness Technology Trends

Health and fitness technology has seen significant advancements in recent years, shaping the way people monitor and improve their well-being. Some of the prominent trends in health and fitness technology include:

1. Wearable Devices: Wearable fitness trackers, smartwatches, and activity monitors have become increasingly popular. These devices track various metrics such as heart rate, steps taken, calories burned, and sleep patterns. They often sync with mobile apps to provide users with insights and data to monitor and improve their health and fitness levels.

2. Fitness Apps: There is a wide range of fitness apps available that offer workout plans, nutrition tracking, and personalized coaching. These apps provide users with guided workouts, track progress, and offer features like goal setting, social sharing, and community support.

3. Virtual Fitness: Virtual fitness platforms and on-demand workouts have gained popularity, especially during the COVID-19 pandemic. These platforms offer a variety of fitness classes, from yoga and HIIT to cycling and dance, that users can access anytime and anywhere. Live-streamed classes and interactive features allow for real-time guidance and engagement.

4. Artificial Intelligence (AI): AI is being utilized in health and fitness technology to provide personalized recommendations, analyze data, and improve workout performance. AI-powered chatbots and virtual trainers can offer tailored fitness plans, answer questions, and provide real-time feedback based on individual needs and goals.

5. Smart Home Gym Equipment: The rise of smart home gym equipment has made it more convenient to exercise at home. These devices, such as connected exercise bikes, treadmills, and strength-training equipment, offer interactive workouts, virtual coaching, and performance tracking capabilities.

6. Sleep Technology: Sleep tracking devices and apps help users monitor their sleep patterns, providing insights into sleep quality, duration, and disturbances. These technologies often offer suggestions for improving sleep habits and overall well-being.

7. Biometric Sensors: Advanced biometric sensors are being integrated into fitness devices and apparel, allowing for real-time monitoring of metrics like heart rate variability, blood oxygen levels, and body temperature. These sensors provide deeper insights into performance, recovery, and overall health.

8. Virtual Reality (VR): VR is being utilized in fitness to create immersive workout experiences. Users can participate in virtual fitness classes, explore virtual environments for outdoor workouts, or engage in gamified workouts for increased motivation and engagement.

9. Telehealth and Remote Monitoring: Telehealth platforms enable remote consultations with healthcare professionals, including fitness trainers and nutritionists. Remote monitoring devices and apps allow for the continuous tracking of vital signs, chronic conditions, and fitness progress, enabling remote supervision and personalized feedback.

10. Data Integration and Analytics: Integrating health and fitness data from various sources, such as wearables, apps, and medical devices, allows for a holistic view of an individual's health. Advanced analytics and machine learning algorithms can process and analyze this data to provide actionable insights and predictive recommendations.

It's important to note that these trends are constantly evolving, and new technologies continue to emerge. Businesses in the health and fitness industry should stay updated on the latest trends to provide innovative and personalized solutions to their customers.

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 Different Features of Health and Fitness app

Workout and exercise

                        This features includes workout plans and videos with explanatory comments. App should be able to create an individual training plan depending on the goals and initial data, as well as easily monitor the athlete’s progress.

App provides information about different exercise with images and  videos on how to perform exercises. It also provided logging features were users will be able to log their work out session. 

Personal trainer apps offer a set of tailormade exercises by enabling the user to choose the difficulty level and the type of exercises that they like the most. 

Most fitness apps come with AI-enabled coaches who can guide you to do your exercises in the right manner. These trainers act like human trainers and can also give you tips to build your strength and stamina. 

Yoga and Meditation

This category includes meditation, yoga, and exercise apps with spiritual practices. The meditation applications are useful to calm down an anxious mind by offering guided & unstructured video.

It may consist of guided meditation sessions, nature sounds, and several step-by-step processes to stay in a peaceful and happy space.

With Yoga feature provides list of Yoga images and videos which can be done at home. 

Diet and Nutrition

    These applications help users control their weight by counting calories consumed and burned, controlling water balance, and encouraging healthy eating habits.
The app will help to create grocery shopping lists, and even collect healthy food recipes.

This will help them in the realtime tracking of their calorie intake and the exact requirement as per their body.

With this food logging app, the users can enter the information of what they had for meals throughout the day and they can see how many calories they have consumed. This way they can have firm control over the calorie intake.

 With this feature, you can present the user with specialized diet tips fit for their eating habits. You can also add recipes that are not only healthy but also tasty as well, motivating the user to follow a healthier eating habit.

Activity tracking

Such applications can count the number of steps and count calories. With geolocation, they can track distance walked.
Users can track their progress of activities on a daily, weekly, or monthly basis and share the information over social media. They can share their workout hours, distance covered, calories burnt, and more on different social media platforms.

This category includes apps that track physical activity, including steps taken, stairs climbed, hours slept, distance traveled, and calories burned.

The wearable device integration is absolutely important for the workout app because it is the best way to track the progress of an exercise routine. The user can track their heart rate, calories burned, goal progress, etc. with the wearable device integration, you can make it convenient for the users to use your app.

Notification & Reminders

Anyone who is working out regularly would never want to miss a session. However, keeping up with the busy lives; sometimes, it does slips out of our mind. In such cases a push notification from the app can be very useful to remind us of our workout session.
Any individual who is working out consistently will never wish to miss a session.

Online consultation & chat

A lot of time, a workout app is not enough. This is why you need to give the users an option to connect and chat with personal trainers near them. By having this network of gym specialists and personal trainers, you will give the users access to better exercise and training experience. Along with this, you can add the workout checklist app feature to it where the user can make their own workout checklist to follow.

Summary of the Features of Health and Fitness app

• Workout and exercise
• Yoga and Meditation
• Diet and Nutrition
• Activity tracking
• Notification & Reminders
• Online consultation & chat

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Introduction to OCR and Google Cloud Vision

What is OCR

        OCR (Optical Character Recognition) is the use of technology to recognize printed or handwritten text characters in digital images of physical documents, such as scanned paper documents.

        The image is converted to a duotone image (ie black and white). Analyze the bright and dark areas of the image

Dark area = character to be recognized

Bright area = background

OCR works by Pattern recognition and feature detection 

Pattern recognition

• Techniques that try to match characters with the character matrix stored in the database 
• Rely on the input characters are consistent fonts, such as OCR A and B

Feature detection

• More sophisticated identification methods 
• Break down characters into "features" such as lines, loops, and intersections

OCR Application

• Passport scanning, ID detect
• Scan document
• Automated data entry, extraction and processing
• Receipt and Invoice Scanning
• Electrical Medical Records
• Forms and Surveys
• Bank : Electronic document processing (checks, etc.)
• ANPR / Traffic : Read vehicle license plate/VIN number
• Logistics: Sort the mail.

Introduction to Artificial Intelligence (AI) and Machine Learning

Internet of Things (IOT) Basics

Google Cloud Vision

    Cloud Vision allows developers to easily integrate vision detection features within applications, including image labeling, face and landmark detection, optical character recognition (OCR), and tagging of explicit content.

Google Cloud – Natural Language Processing (NLP)

Source : Google Cloud Vision

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Different sensors used in fitness trackers

Different sensors used in fitness trackers   

          Smartwatches with Fitness trackers have become essential lifestyle devices that helps track how active you are along with basic health parameters.

The smartwatches do a lot more than showing time, show notifications on your wrist. They're everything in one: a fitness tracker, a wallet, and in some cases, even making phone calls.

            A smartwatch can also save your life with elevated heart rate alerts and automatically connect you to emergency services if you fall. Electrocardiogram (ECG) and blood oxygen (SpO2) readings are perks of certain premium models, too. It still has a compass, fall detection and GPS.

Following are the different sensors used in fitness trackers:

Ambient light sensor: This sensor is also used in mobile devices to increase or decrease the screen brightness, thus saving your battery life. This sensor tweaks display brightness based on the surrounding light for better battery life.

3 axis accelerometer: This is an electromechanical device that senses gravity, as well as linear accelerations, detects movement, and tracks direction. This track's forward and backward movement by sensing gravity and determine the body’s orientation, position, and also rate of change of speed.

Altimeter: This sensor uses atmospheric pressure to sense any changes in the altitude. Detects Change in height, are you climbing stairs or going down to calculate calories count. 

Barometer : This measures and shows the atmospheric pressure, thus you can know whether it is going to be sunny or rainy day.

Best Fitness Tracker and Smart Watch

Optical heart rate: This sensor detects heartbeats per minute. The device with an optical HR sensor calculates your heartbeat  per minute using a special algorithm. This sensor uses light to check the speed of blood flow on the wrist. When the heartbeats, blood moves quickly inside thus less light is reflected back to the sensor and is detected as a heartbeat 

SpO2: This sensor used to monitor and measure blood oxygen levels. It uses LEDs as a light source to emit light into the tissue and a photodetector is used to collect the light back from the skin and measure how well the oxygen is supplied to each part of your body from your heart. 

Bioimpedance sensor: This sensor is used in Smart weighing scales to measure your body composition such as the total body fat w.r.t your lean body mass.

Proximity sensor : These sensors saves battery and wakes the display when needed.  It helps in lowering the power consumption by putting the device to sleep If you are not wearing the fitness tracker, this sensor enables the device to sleep and save battery when not in use and turns off display

Compass : It helps in direction and Maps. It shows the direction of magnetic north and bearings from it. A compass helps Map applications to run on a smartwatch and also gives the device a sense of direction.

ECG sensor: This sensor is to detect the minute electrical impulse that your heart sends out with every heartbeat This sensor detects this minute heart signal through the electrodes on the wearable.

GPS : It works by tracking your exact location while you are walking or running by calculating the distance between series of GPS satellites. It helps in detecting how much you are running, the location of wearable, and tracks your activity.

LTE : A LTE enabled device, simply means that is has built-in mobile connection i.e., you can make/receive calls directly from the device itself.

Gyroscope : Used to detect motion . It is used with other sensors to determine whether you are actually running or simply jogging.

UV sensor: It measures exposure to harmful sunlight. The UV sensor monitors the sunlight and alerts when you’re absorbing dangerous UV radiation whether the sunlight outdoors is harmful or not.

Magnetometer :  The sensor measures the magnetic field of the earth and can also be used as a compass. Works along with the GPS and compass to determine the exact  coordinates of your location 

Electrodermal activity sensor : It measure stress along with a heart rate tracker, ECG, and skin temperature sensor. It detects small electrical changes in the sweat level of your skin and helps you manage your stress.

Best Fitness Tracker and Smart Watch

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Introduction to AR Core

What is AR (Augmented Reality)

• Blend real world in to the digital world

• Integrate virtual content with the real world as seen through phone's camera

ARCore is Google’s platform for building augmented reality experiences
 

What is Google’s Tango Project (Prior to AR Core)

        ARCore has its origins in Tango, which is/was a more advanced AR toolkit that used special sensors built into consumer mobile device.
        Google’s (Peanut phone , Yellow Stone tablet) , Intel’s Real sense Smart phone , Lenovo Phab -2 , Asus Zen phone are equipped  with special sensors
        Later Google stopped Tango project as ARCore is evolved with less dependent on sensors as compared to Tango

Hardware of Phone used by ARCore

• Fundamental concepts behind ARCore

• Motion tracking

• Feature points (through camera) + Motion sensors (through IMU: Accelero , Gyro)

• Point , PointCloud , Pose are some of the classes exposed by ARCore SDK we can see how  user's position is tracked in relation to the feature points identified on the real couch.

• Environmental understanding 

• Uses technique called meshing 

• Cluster of feature points used and returned as planes to applications along with each plane’s boundary

How does AR Core works

AR Core fundamentally does two things

    1. Motion Tracking
        Building it’s own understanding of real world (Environmental understanding , Light Estimation , Orientation points , Anchors , Trackables

    2. Environmental limitations
        For now, limitations that may hinder accurate understanding of surfaces include:

• Flat surfaces without texture, such as a white desk

• Environments with dim lighting

• Extremely bright environments

• Transparent or reflective surfaces like glass

• Dynamic or moving surfaces, such as blades of grass or ripples in water

        When users encounter environmental limitations, indicate what went wrong and point them in the right direction.   

            AR application that has identified a real-world surface through meshing. The plane is identified by the white dots. In the background, we can see how the user has already placed various virtual objects on the surface.

Light estimation

        Average intensity and color correction of a given camera image
Scene of realism is increased by applying the same light condition to virtual objects LightEstimate , LightEstimate.State are some of the classes used to get lightning condition User Interaction , Orientation points , Anchors and Trackables.
        Takes an (x,y) coordinate corresponding to the phone's screen
Projects ray into camera’s view of the real world
        Returns Plane/feature points that the ray intersects and Pose (kind of OpenGL model matrices) of that intersection in world space
HitResult , Pose , Anchor (fixed location and orientation of real world) are some of the classes provided by ARCore in this context
Trackable (interface) is something that ARCore can track and that Anchors can be attached to 

Note: 
        Because ARCore uses clusters of feature points to detect the surface's angle, surfaces without texture, such as a white wall, may not be detected properly.
        To reduce CPU costs, reuse anchors when possible and detach anchors that you no longer need.

Link for reference: https://developers.google.com/ar/develop/java/cloud-anchors/overview-android

References:
Samples: https://github.com/google-ar/sceneform-android-sdk.git 
https://developers.google.com/ar/develop/java/quickstart

Books on ARCore

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Android A11 features

                       

             Android 11 introduces great new features and APIs for developers. Android 11 focus more on People-centric and expressive, with a new controls space and more privacy features.
            Extend your apps with conversation notifications and bubbles, try one-time permissions, surface devices and media in the controls. Work faster with tools like compatibility toggles, ADB incremental installs, and more!

Lets look into Android 11 features

Conversation notifications

                There are now three notification categories: Conversations, Alerting, and Silent. The Conversations section, quite obviously, houses all your conversations. This would mean any app where you are directly communicating with someone else, including text messages and chat apps.     

            Meanwhile, the Alerting and Silent sections act as they have before in Android 10. You can also easily silence notifications from certain apps, which would push all future notifications to the Silent section. With Android 11, you now have more control over notifications than you ever had previously.

Notification history

            In Android 11! A new feature gives you the option of saving every single notification that landed on your phone over the past 24 hours. You can check the running list, find the notification you accidentally swiped, and see what you missed.

Related: Here’s a list of Android 11 phones

Chat bubbles in Android 11

             For all chat applications Android, you already know how chat bubbles work. With Messenger, a “chat head” appears on your phone that overlays on top of pretty much every other app. A quick tap of the icon launches the chat and then you can minimize the chat back to an icon. Done with the conversation? You can remove the chat head until the next conversation starts

Android 11 screen recorder

            The screen recorder function lives in the Quick Settings tiles. You tap the Screen Record feature which gives you a few options before you start recording. For example, you can choose whether or not your screen-taps should also be recorded and whether the phone should capture audio, too.

Media controls

                If you are playing music on your Android 10 phone, a music player appears at the top of your notifications drawer. Of course, with Android 11, that section of the drawer is now reserved for conversations, so the media player needed to move. Google decided to move it one rung up to the Quick Settings section.    
                When you swipe down your notification drawer, the media controller will be pretty small. It will show you the app it’s related to, cover art, basic controls, and on which system the media is playing. If you pull down again on the drawer, the alert expands and shows the information

Smart device controls

                Google added a new section in Android 11 that allows you to easily control your various devices without needing to open an app.

                You can hold down the power button to launch the new tool. At the top, you’ll find the usual power features, but underneath, you’ll see a lot more options. There’s a Google Pay shortcut that allows you to quickly choose which payment method you want your next contactless transaction to use. Under that, you’ll see a bunch of buttons connected to your various smart home products.
                
        The Device Controls feature, available starting in Android R, allows the user to quickly view and control external devices such as lights, thermostats, and cameras from the Android power menu. Device aggregators (for example, Google Home) and third-party vendor apps can provide devices for display in this space.​

One-time permissions and auto-reset

            Android 11 gives the user even more control by allowing them to give permissions only for that specific session.
            Similarly, Android 11 will now “auto-reset” apps you haven’t used in a while. If you granted location data permissions to an app that you haven’t opened up in a long time, Android will now revoke all permissions. Next time you open the app, you’ll need to approve those permissions again. 

Dark Theme 

            With Android 11, users can now schedule the dark theme using one of two different metrics. You can schedule a dark theme to turn on or off when the sun sets or rises. You can also set up a custom schedule for dark mode activation if you wish.

 

Some of the other features are 

Concurrent Camera Streaming : Many devices have the hardware capability to stream multiple camera sensors concurrently.

Camera Bokeh : to make the bokeh feature available to third-party apps​

Generic Kernel Image​ : Android R introduces the Generic Kernel Image (GKI), which addresses kernel fragmentation by unifying the core kernel and moving SoC and board support out of the core kernel into loadable modules.​

Device Type Limit​ : In Android R, no limit on the number of audio device types to allow new audio device types to be added​

Soft restarts​ : Android R supports soft restarts, which are runtime restarts of processes in the user space used to apply updates that require a reboot (for example, updates to APEX packages).​

Zombie permissions : Android will automatically revoke an app’s permissions after an undetermined time of inactivity—somewhere between 60 and 90 days. Launching an app within that time reinstates any permissions you’ve granted​

Notification/Sound Muting​ : Device vibration and sounds can hurt image and video quality, especially for cameras with optical image stabilization module​. camera app could use the (DnD) APIs to mute the vibration and sounds
Offline Processing​: Today camera apps must wait for all requests to be fully processed before it can disconnect from the camera or switch to a different configuration, The offline processing API allows the camera HAL to perform post-processing in the background to improve the latency of mode switching or camera closing​

Android 11 updates via Play Store

            Each year, Google releases the latest version of Android. Each month, it pushes out the latest Android security patch. Both of these updates get funneled to your phone either by your carrier or equipment manufacturer. Because of this, some phones get many updates very quickly, while others either get them much slower or not at all.o counteract this, Android 11 gives more power related to updates over to the Google Play Store. This allows Google to bypass carriers and OEMs entirely and push out updates to everyone.

App-pinning to the share sheet

            You can now pin apps to your share sheet in order to easily access them whenever you want to share something.This feature allows you, the user, to control which apps appear at the top of the list when you want to share something.

Improved prediction tools

            Android 11 will seemingly reduce the work you need to do on your phone, by predicting your habits and patterns.
            One such example of this is smart folders, so you can let Android 11 automatically sort your apps into folders of similar apps, like games or productivity tools.
            App suggestions is also tweaked to suggest apps based on your routine - for example, if you always log onto your Fitbit app first thing in the morning to examine your sleep habits, the phone will now automatically pop that app into the Home screen in the morning so it's easily accessible.
            Finally, apparently the Smart Reply feature already usable in Android phones has received some tweaks. This mode suggests some automatic responses when you receive a message, letting you reply with one tap (if any of the responses are appropriate) but it's not clear what's new here.

New phones coming with Android 11

• OnePlus 8

• Oppo Find X2 and Find X2 Pro

• Realme X50 Pro

• Xiaomi Mi 10 and Mi 10 Pro

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