Mobile Journalism

SceneTap: Old Technology, New Tricks

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I recently discovered SceneTap while reading a Gizmodo article about useful apps to have during a night out, and, at first, I was amazed it existed.  But when I thought about it more, I said to myself, “Why shouldn’t this exist?” SceneTap uses technology that was mostly useful to businesses only and put it in the pocket of everyday smartphone users.

SceneTap is an app for iOS and Android that provides real-time information on how many people are present in a location at any given time. Unfortunately, the app only works in a handful of places (mostly bars) that are enabled with SceneTap’s hardware and software, so its functionality is limited at this point. However, I think there is room for potential growth and expansion of the app’s capabilities that could make SceneTap, or an app using similar technology, a useful tool in areas other than nightlife entertainment.

CNN reports on the app here:

How It Works:

SceneTap uses people counting software and anonymous video analytics (AVA) technology to estimate how many people are in a room, how old they are, and what their genders are.  The counting sensors SceneTap uses to determine crowd size are similar to the counting technologies used by retail stores to keep track of how many customers they have in a day.  AVA technology is used to take a video of a crowd, then analyzes faces to determine gender and estimate age using pattern detection.

One of the biggest issues technologies such as this face is the question of privacy. SceneTap’s Frequently Asked Questions page (FAQ) does a good job of quelling a few initial fears a user may have in this regard.

One may find the idea of real-time knowledge of whether an individual man or woman just walked into an establishment worrisome and fodder for unwanted attention, but the FAQ says this does not happen. According to the site, “All of the demographic data that is streamed to the public is non-individualized based on a rolling 30 minute period of activity. For example, if a user views the demographic information at 8:37pm, it will display the demographic information on people that entered the place between 8:07 – 8:37pm. Data is aggregated over a period of time and updated in blocks to add another layer of anonymity.”

One may also naturally be concerned that the videos taken by AVA cameras are stored or shared, but according to SceneTap’s FAQ that is not the case. According to the website, “Each video frame is processed to detect the presence of faces, and is then destroyed in real time.”

SceneTap’s website also addresses the concern that its software can identify you personally, but that is also not the case.  SceneTap uses facial detection software, not facial recognition software, and the difference is key.

Facial recognition software compares your face against a database to identify you personally, while facial detection software merely uses pattern detection algorithms to determine whether it has scanned a human face. You have probably already encountered and utilized both of these technologies, whether you’re aware of it or not.  Facebook uses facial recognition software to suggest tags in photos, while digital cameras use facial detection software to help focus your photo on human subjects.

Facial detection software at work

Still not satisfied? More information on SceneTap and your privacy can be found in this Privacy Scene interview with Andrew Cummins, SceneTap’s chief strategy officer, and also in this report on privacy and AVA by Ann Cavoukian, the information and privacy commissioner of Ontario.

SceneTap and Journalism:

SceneTap’s technology could prove to be a very useful tool for individual journalists as well as news organizations.

If hardware similar to that of SceneTap was installed in places where newsworthy events occur, such as conference centers or other public spaces, news organizations could potentially save money and time by determining how many reporters to send out based on the crowd analysis.

Individual journalists could also potentially benefit from this technology.  A reporter may find an angle based on the age and gender of people present at an event. For instance, if an unusual or unexpected amount of older men is present in a location where a feminist rally is occurring, the reporter could infer that these may be protesters, members of an allied organization, or everyday individuals reflecting a climate change in feminism.  This would allow the reporter to prepare more thoughtful and relevant questions, thus enriching his or her article.

SceneTap also provides opportunities for user generated content that may be useful to a journalist.  People can check in, leave comments and add photos to location pages within the app.  Journalists can use this information to feel out a location before they arrive, and maybe even use some of those photos and comments in their stories, with permission.  If reporters don’t quote people directly from these comments, they can at least identify commenters as potential sources who are already present and willing to share their thoughts.

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