A Google patent application published in the last week describes how Google might be using Mobile data from phones to map indoor spaces, combining the technologies behind Behavio, with traffic monitoring from Zipdash to better understand spaces that many people navigate through while carrying a mobile device that connects to the internet with wireless signals and carries sensor data that can indicate the location and movements of those devices.
The patent tells us that current approaches to determine indoor locations of mobile devices are based on interior scans of wireless access points. Theses scans could be used to build a database that can model an indoor space by determining locations of the access points and their corresponding signal strengths at those locations. To create a database like this, an indoor wireless location provider would have to conduct site surveys at selected locations.
We’ve all read about Google working to build self-driving cars, and I’ve written about Google building Google Maps programs to help people navigate to different places.
A Google patent application published this week takes a closer look at computers in cars, and the many sensors that are connected to those, and it discusses how automotive computing systems that include such things as:
…network based applications including navigation, voice search, media streaming capabilities, and the like.
The patent mentions On board diagnostics (OBD) standards in the automotive industry were made became available with engine computer systems that showed up in the 1980s.
A couple of interesting patent applications surfaced at Google recently, involving the use of photography in Local Search, to identify whether or not businesses actually exist, or might be closed, or might be Web Spam.
The first of these looks at Street Views images, and is:
Google finds terms and phrases to associate with entities that can be considered terms of interest for businesses, locations, and other entities. These terms can influence what shows up in search results and in knowledge panels for those entities. Consider it part of a growing knowledge base of concepts, entities, attributes for entities, and keywords that shape the new Google after Hummingbird. Semantics play a role as things that specific entities are known for are identified.
For example, the Warrenton, Virginia, Red Truck Bakery (local to me) is known for:
In my college days, I cooked at some local restaurants (free meals made it an attractive option for a starving college student). One of the restaurants was in the center of town, at one end of Main Street, and it was a popular place for local residents who returned over and over. It had a great reputation, and word-of-mouth propelled advertising for the place. Another dining venue I worked at was outside of the center of town, nearby an interstate highway. It didn’t have a great reputation, and very few regular customers, except for people who would stop during mealtime from the busy interstate. The “food” sign from the highway attracted most of the traffic to its dining room.
Funny thing is that most of the regulars that frequented the first restaurant rarely had to look up its location, because it was so well known. Most of the people who visited the second restaurant had never been there before, and relied upon the highway sign. There’s another restaurant in that location now, and I have no doubt that many people find it via maps or navigation on their mobile devices or in-car navigation. I mention this because I have some issues with a recently granted Google patent.
Google has come under fire the last year or so from critics who claim that the search engine has been providing too many pages from some of the same domains in search results. It appears that this has had them looking at ways that they could provide more diversity within those results. A patent granted to Google earlier this year describes one approach that could have an impact on both local search rankings and Web rankings for authority pages for business entities.
The impact of this approach would be that when these authority pages ranked highly in both Web results and local search results, Google might merge listings for the two, so that the Web search result no longer appears within search results for a specific query and the local search result is potentially boosted higher in results as well.
In the past, I’ve written about How Google Universal Search and Blended Results May Work, describing how Google might decide when and where to include multiple listings within Web search results from different vertical search types, such as local results, images, news articles, videos, and others. Each of these different types of results might be ranked based upon their relevance to a query, and might be included within results based upon how meaningful those results might be to the query and the intent of a searcher.
My neighbor has run over my last two phonebooks, and rendered them virtually unusable. We share the same driveway, and it appears that running over phonebooks, and then backing up to make sure they are really dead has officially become a custom in Virginia, or at least in my neighborhood. It’s OK though, since I can’t remember the last time I’ve used a phone book. I may have a couple of times earlier this century, but I’m not sure. I definitely haven’t used one in in the past couple of years (my neighbor keeps killing them).
On the Fourth of July, Apple published a patent application that describes Routes based on User Ratings and Real Time Accident Reporting. Both Apple and Google have been using GPS information to monitor and report upon gridlock and traffic speed estimates, but imagine both providing a richer and fuller social experience involving the world around them. Imagine being able to choose different routes and see social annotations added to different options on those routes. Here’s a screenshot from Apple’s patent filing:
Are Google’s query-based social circles the answer to Facebook’s Graph Search?
Not too long ago, Facebook launched its Graph Search, which enables people to search for things like “My Friends who live in San Francisco,” and My Friends who like Surfing,’ and “Places my Friends like.”
Imagine if Google Plus allowed you to perform searches such as, “People who take the same bus as me into the city,” or “People who like to eat at the Red Truck Bakery,” or “People attending the Dave Matthews Band Concert next Friday,” and creates in response a social network circle that other people might be invited to join, even temporarily, or who could join anonymously. Or Google Plus may dynamically create such a query-based social circle which it may recommend that you share through as you create a post about a music festival you’re going to, or a meal you’re reviewing from a local hotel.
The image above from the patent filing shows a query-based circle for a “Music Festival” and a query-based circle for a “Grand Hotel,” as well as a button to only display query-based circles in the interface.