It was the middle of a Friday afternoon prayer. The masjid was silent, save for the soft murmur of the Imam. Suddenly, from the pocket of the man sitting directly behind me, a loud, upbeat pop song blared out at maximum volume. He fumbled, clearly mortified, trying to swipe his screen while the sound echoed against the walls. The embarrassment was palpable. I looked down at my own device, realized I had almost forgotten to toggle my own 'Do Not Disturb' mode, and knew there had to be a better way to handle these transitions.
That moment of public friction is the reason I built Muffle. We live in an era where our phones are expected to be context-aware, yet we are still manually toggling sound profiles like it is 2012. The problem isn't that we don't have the tools; it is that the tools require active human intervention. You arrive at a meeting, you forget to mute. You leave the meeting, you forget to unmute, missing important calls for hours afterward. Most existing solutions are either battery-hungry monsters that keep the GPS radio pinned to the high-accuracy setting or rely on third-party cloud services that compromise privacy. I wanted a solution that felt invisible, worked entirely on-device, and didn't turn my phone into a space heater.
When I started architecting Muffle, the biggest technical hurdle was managing background tasks without destroying the user's battery life. Android has become increasingly aggressive with background execution limits, and for good reason. If you let a service run wild, the OS kills it. If you don't use the right primitives, the user complains about battery drain. I decided to lean heavily on WorkManager for the heavy lifting and a Foreground Service for the immediate, time-sensitive sound state changes. The primary challenge was the Prayer Time trigger. Unlike a simple calendar event, prayer times shift every single day based on geolocation. Using a PeriodicWorkRequest to recalculate these times every 24 hours was the logical choice, as it respects system-imposed power constraints while ensuring the data is always fresh.
For the actual sound state management, I chose to implement a Foreground Service that listens for specific broadcasts. Specifically, I needed to handle ACTION_NOTIFICATION_POLICY_ACCESS_GRANTED to interact with the system's AudioManager and NotificationManager. Using a Foreground Service is technically mandatory for any task that requires immediate, user-visible interaction, but it also provides a persistent notification that keeps the process alive in the eyes of the Android system. I avoided the common mistake of polling for location. Instead, I used the GeofencingClient, which offloads the heavy lifting of location monitoring to the Google Play Services library. By setting a transition type to GEOFENCE_TRANSITION_ENTER and GEOFENCE_TRANSITION_EXIT, I only wake up my code when the user actually crosses a threshold.
kotlin
val geofencingRequest = GeofencingRequest.Builder()
.addGeofences(geofencesList)
.setInitialTrigger(GeofencingRequest.INITIAL_TRIGGER_ENTER)
.build()
val pendingIntent = PendingIntent.getBroadcast(
context, 0, intent, PendingIntent.FLAG_UPDATE_CURRENT or PendingIntent.FLAG_IMMUTABLE
)
geofencingClient.addGeofences(geofencingRequest, pendingIntent)
This approach means that Muffle consumes almost zero energy when the user is stationary. The system handles the location check, and my code only reacts when an actual event occurs. It is an event-driven architecture rather than a polling-driven one, which is the only way to build a sustainable background app on modern Android.
What surprised me most during development was how fickle the AlarmManager can be when the device enters 'Doze' mode. I initially assumed that setExactAndAllowWhileIdle would be enough to trigger sound changes for precise prayer times. I was wrong. On certain OEM skins like MIUI or Funtouch OS, the manufacturer's aggressive battery management processes often strip away even these 'idle-safe' alarms. I spent three days debugging why a user in Pakistan wasn't seeing their phone silence during Maghrib, only to realize the OS was killing my background receiver entirely. The fix wasn't just code; it was user education. I had to build an internal 'battery optimization check' within the app that directs users to the 'Don't Kill My App' website resources for their specific device model. It taught me that on Android, technical implementation is only 60% of the battle; the rest is navigating the fragmented landscape of OEM-specific power policies.
If I were to start over, I would move away from relying on AlarmManager for everything and instead use a more hybrid approach using WorkManager exclusively for scheduling, combined with a Room database to act as the single source of truth for the device's state. I initially tried to cache the current sound state in memory, which caused issues after phone reboots. When the device restarts, the Foreground Service needs to re-evaluate the environment immediately. By storing the active routine in a local Room database, I ensured that as soon as the BOOT_COMPLETED broadcast is received, the app queries the DB and re-applies the correct audio profile without the user ever knowing the phone had restarted. Relying on persistent storage for state instead of volatile memory was the turning point for the app's stability.
For any developer building background-oriented apps, the biggest takeaway is this: do not fight the system. If you try to bypass battery optimizations, the system will eventually win, and the user will uninstall your app. Instead, embrace the constraints of the WorkManager library. Treat the Android OS as a gatekeeper that you are collaborating with, not a hurdle you need to jump over. When you design your features, ask yourself: 'Does this really need to run now, or can it wait for the next maintenance window?' Most of the time, it can wait. By offloading tasks to the system scheduler, you gain the benefit of system-level battery optimizations that you could never replicate by writing your own background loops.
It is also worth noting that privacy is a feature in itself. By architecting the app to store everything locally and avoiding external API calls for logic, I was able to build something that users trust. They know their location data and their prayer habits aren't being sold or tracked in the cloud. That trust is what keeps the app installed. If you are interested in how I implemented the local-first storage or want to see the routine conflict logic, you can check out the implementation of Muffle here: https://play.google.com/store/apps/details?id=com.muffle.app. Developing for the background is challenging, but when you get it right, the result is a tool that genuinely makes the user's day-to-day life a little bit easier.
Top comments (1)
재부팅 뒤에도 활성 루틴을 다시 판단하도록 메모리 상태와 영속 상태를 구분한 경험이 와닿습니다. 회의와 위치 기반 루틴이 겹치거나 사용자가 중간에 소리 모드를 직접 바꿨을 때, 어떤 루틴이 끝나야 이전 모드로 돌아갈지 우선권을 정하는 기준도 궁금합니다.