Apps Like dB Meter - Noise Level Meter for iPhone and iPad
Ranked alternatives
Showing 81–100 of 1,000 ranked alternatives.

Blowly Cleaner: Clear Wave
Yury Shildiner
Clean speakers with sound waves
Clean speakers and headphones using sound waves to remove dust and moisture without disassembly. Perform automatic or manual cleaning with scheduled reminders. Conduct basic sound tests to check speaker functionality.







Clean Wave - Clear Speaker
David Krejci
Play sounds, speakers, measure noise
Play sounds at defined frequencies between 0Hz and 25kHz. Use the noise meter to measure sound levels. Test speakers with quality audio for sound output.

Clean Tune - Speaker Cleaner
DREAMTEAM APPS sp. z o.o.
Play sounds at set frequencies
Play sounds at specific frequencies. phone speakers from water with a single button press. Measure current noise levels using microphone access.



Static - The Noise Generator
Thaddeus Ternes
Play soothing sounds to rest or focus
Play calming sounds like white , pink , campfire, or ocean waves to aid relaxation or focus. Adjust volume and select sounds remotely. Access a variety of soundscapes in the full version.

SPLnFFT Noise Meter
Fabien Lefebvre
Sound level meter frequency analyzer generator
The app measures sound levels using a digital display for sound power and an analog display for fast mode. It also features real-time FFT frequency analysis with highlighted predominant frequencies and their power.



Clear Wave - Remove Water
Davin App LTD
Test speakers and microphone quality
Test audio output and input quality by playing sound waves and analyzing speaker clarity. Detect microphone issues through voice recordings. Clean speakers and or dust with built-in tools.

Decibel Meter-Noise monitoring
Mirarobot Science & Technology Co., Ltd.
Measure noise, track decibels, generate reports
Measure ambient noise levels in real time and save data locally. Generate visual reports from collected data. Record noise changes with camera forensics.
How we rank alternatives
Apps are ranked by functional similarity, category fit, rating confidence, and popularity.