Optimizing an application to reduce resource consumption while maintaining functionality is crucial, especially in automotive software. For example, I worked on an Android-based in-vehicle infotainment (IVI) system that operated on a System on Chip (SoC) platform with multiple displays. The system needed to perform efficiently, minimize latency, and ensure low power consumption.

To achieve this, I started with profiling and identification, utilizing performance profiling tools in Android Studio, such as the profiler and system trace, to identify bottlenecks. I monitored CPU usage, memory consumption, and power consumption to pinpoint areas of high resource usage.

Next, I concentrated on optimizing CPU usage by managing threads effectively. I moved tasks off the main UI thread to background threads, which helped reduce latency. I also applied efficient coding practices to avoid unnecessary computations and loops, employing efficient data structures and algorithms to minimize CPU overhead.

To decrease memory consumption, I used tools like LeakCanary to detect and fix memory leaks. I managed the lifecycle of activities and fragments properly to avoid retaining unnecessary references. Additionally, I optimized bitmap loading by resizing images and using BitmapFactory options, and I implemented caching for frequently used bitmaps.

I also streamlined I/O operations to reduce latency and enhance performance. For power optimization, I utilized power profiling tools to monitor battery usage and identify components that consumed excessive power. I optimized the use of wake locks to ensure they were held only when necessary, preventing unnecessary battery drain.

After implementing these optimizations, the IVI system demonstrated significant improvements in performance, reduced CPU usage, lower memory consumption, and enhanced power efficiency. This resulted in a smoother user experience and extended battery life.