Hello, everyone. My name is Shanu Sahadevan and today I will be presenting on maximizing IoT app efficiency proven techniques for seamless performance across devices with IoT apps becoming an essential part of our daily lives, ensuring their efficient and consistent performance is more important than ever. By the end of this presentation, you will have actionable insight to build faster, more efficient IoT apps that deliver exceptional experiences. Let's dive in. Here is what we will be covering in today's session. We will start with an introduction to why performance optimization is crucial for IoT apps. Next, we will dive into specific optimization strategies, starting with asynchronous performance, followed by battery and memory optimization. We will also look at reducing app size to make it lightweight, along with tips for optimizing database interactions. Towards the end, I will introduce some essential tools and metrics to help you profile and monitor your app's performance. Let's get started. Let's start by exploring why performance optimization is so critical in the context of IoT apps. First, app performance directly impacts user experience. Users expect IoT apps to be fast, Responsive and reliable. Poor performance can lead to dissatisfaction and may lead users to abandon the app. IoT apps come with unique challenges, including the need to handle real time data, operate on resource constrained devices, and adapt to a wide range of hardware environments. The goal of optimization is to overcome these challenges and create apps that are fast, efficient, and dependable. Let's begin with one of the most foundational elements of optimization, asynchronous performance. In the IoT world, apps often need to handle real time data processing, continuous device communication, and background tasks, all without freezing or lagging. To achieve this, we must ensure that heavy operations don't block the main thread, which is responsible for the user interface. Kotlin coroutines offers a modern and efficient way to handle asynchronous programming in Android. They provide constructs like launch for background tasks and async for concurrent operations with structured concurrency, making the code more readable and manageable. For long running tasks, WorkManager is an excellent solution. It ensures tasks like data synchronization or periodic updates run without any problems, even if the app is closed or device restarts. This is particularly useful in IoT apps where periodic communication with devices or server is common. Always profile your app using tools like Android Profiler to identify any inefficiencies or bottlenecks in threat usage. Lastly, remember that not all operations need to be async. Balance is key. Operations that are quick and won't block the main thread can remain synchronous to avoid unnecessary complexity. It is very important to ensure that apps not drain the device battery. Let's look at how we can optimize battery performance. First, managing background tasks effectively is key. Instead of constantly running tasks, use Android's job scheduler or work manager. These APIs help you schedule tasks intelligently based on system conditions like network availability or battery levels, ensuring minimal impact on battery life. Next, sensor and GPS usage is a common culprit for battery drain in IoT apps. To optimize batch sensor data to minimize device wakeups and choose coarse location for tasks where high accuracy isn't necessary, such as geofencing. By combining these strategies, we can design IoT apps that provide excellent functionality while respecting the device limited battery resource. Memory management is another critical factor in maintaining smooth app performance, especially in data intensive IoT applications. Let's dive into that. Poor memory management can lead to issues like lagging, freezing, or even crashes, especially on resource constrained devices. Let's break down the challenges and how to address them effectively. First, let's talk about the challenge of high data throughput in IoT. IoT apps constantly receive and process data from devices, which can quickly exhaust memory if not managed efficiently. This is compounded by the fact that many IoT apps require frequent updates, further increasing the load on memory. To address these challenges, start by using weak references where appropriate. Weak references can help to ensure objects are garbage collected when no longer needed. This prevents memory leaks. Next, You need to actively monitor your app's heap usage. Tools like LeakHandlery are invaluable here. LeakHandlery can automatically detect and report memory leaks during development, making it easier to identify problematic code and fix before release. Another effective optimization strategy is to implement object pooling. For objects that are frequently created and discarded, like temporary data containers or UI components. object pooling can help to reduce the overhead of memory allocation and garbage collection. In summary, efficient memory management ensures that your IoT app runs smoothly even under heavy data loads and frequent updates. Reducing app size is especially important for IoT devices as many of these devices have limited storage. To achieve this, let's look at a few techniques. First, enable ProGuard or R8 for code shrinking and optimization. These tools help to remove unused code, classes, and methods from your app, reducing its size significantly. Next, use Android App Bundle. This format allows the Play Store to deliver only the code and resources required for a specific device configuration, such as screen size, language, or architecture. Another crucial technique is to compress and optimize media assets. For instance, resize and compress images without sacrificing quality using tools like TinyPNG, or choose modern formats like Buffy. Finally, use the APK Analyzer tool in Android Studio to identify and analyze the largest contributors to your app size. By implementing these techniques, you can create lightweight IoT apps that are easier to download, install, and run on a variety of devices, ultimately improving user experience and accessibility. Let's move on to the database performance optimization. Efficient database performance is a cornerstone of a high performing IoT app. Databases in IoT apps often face common bottlenecks, such as frequent read and write operations due to the need for real time data synchronization with IoT devices. To tackle these challenges, let's explore some optimization techniques. First, use Room, Android's recommended database library. which abstracts XULite and provide robust and easy to use framework for database operations. With Room, you can implement proper indexing on frequently queried columns, indexing speed up data retrieval. Second, for scenarios where large data sets needs to be displayed or processed, pagination. Finally, for frequently accessed data that doesn't change often, consider preloading it into memory where feasible. Now let's explore the tools and metrics that can help you monitor and refine your app's performance. To ensure the best performance for your IoT apps, it's critical to have the right tools in your toolkit. First, Android Profiler is an all in one tool available in Android Studio. It provides real time insight into your app's CPU, memory, and network usage, helping you understand how your app performs under various conditions. Android Next, leak henry is invaluable for detecting memory leaks during development. Memory leaks can silently degrade performance over time, especially in IoT apps handling frequent updates and real time data. For monitoring performance in production environments, Firebase Performance Monitoring is a great choice. It tracks metrics like app startup time, network request performance, and latency, providing you with actionable insight from real user data. The network profiler, part of Android profiler, is a specialized tool for analyzing network activity. By leveraging these tools and tracking the right metrics, You can continuously refine your app performance, ensuring it delivers a seamless and efficient experience for your users. As we wrap up, let's revisit the key insights from today's session. First and foremost, always prioritize user experience. Your app must be responsive as poor performance can directly impact user satisfaction and retention. Modern tools and techniques can greatly enhance app performance. Kotlin coroutines for async tasks, room for database efficiency, And retrofit for streamlined network request are highly effective solutions in the IoT space. Monitoring is an ongoing process. Use tool like Android Profiler to track CPU, memory, and network usage. And Leak Canary to catch memory leaks early. These tools provide actionable insights for continual improvement. Always minimize resource usage. Also, reducing app size make it more practical for users with storage constraints. Finally, remember that optimization is not a one time task. It is an iterative process. By keeping these takeaways in mind, you can build IoT apps that are not only high performing, but also delight users with their reliability and efficiency. Thank you for taking the time to explore this presentation. Your attention and interest mean a lot and I hope the insights shared today were valuable. Thank you.