Sound-Mapping Restaurant Apps

iHEARu Uses Crowdsourcing to Measure Noise Levels in Restaurants

You've surely heard of restaurant apps that allow you to browse and locate restaurants based on proximity, price preference or type of cuisine, but iHEARu is a completely novel app that uses crowdsourcing data to filter restaurants based on how noisy they are.

The iHEARu app allows users to harness decibel data of restaurants, cafes and bars and upload the information onto the app's database. Others can then take advantage of the array of data sets available on the app to select a restaurant that suits their needs.

There's no question that noise levels can make or break a restaurant experience, as the amount of noise a diner is willing to put up with for a Valentine's Day dinner differs from the extent of sound one might be willing to accept for a meal with friends. This app also happens to be developed by noted audiologist Kelly Tremblay, giving it a high degree of credibility.

Given that excessive noise can ruin a lunch or dinner outing, this app could prove to be a useful tool for people who want to be able to control this underrated aspect of the restaurant experience.
Trend Themes
1. Crowdsourcing Data - Using crowdsourced decibel data to filter and select restaurants based on noise levels.
2. Personalized Restaurant Selection - Enabling users to find restaurants that suit their noise preference and specific dining occasions.
3. Credibility in Noise Measurement - Offering a credible app developed by an audiologist, providing accurate noise level data.
Industry Implications
1. Restaurant Industry - The app provides an opportunity for restaurants to cater to customers' noise preference and improve overall dining experiences.
2. Technology Industry - Developing innovative apps like iHEARu that can harness crowdsourcing data for personalized recommendations.
3. Audio and Sound Engineering Industry - The app opens avenues for sound engineers to collaborate and create noise control solutions for the restaurant industry.

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