Are you there yet?

Plenty of people love the Weasley family’s clock from the Harry Potter books and films. It shows where members of the family are at any given time. Instead of numbers giving the time, the clock face has locations where someone might be (home, school, shopping) and the many hands on the clock show the family members. The wizarding world uses magic to make their whereabouts clock work, but muggles (and squibs) can use mobile network data to build a simple version, and use Bayesian networks to improve it.

A cell phone tower looking up from inside to a blue sky

Your mobile phone is in contact with several cell towers in the mobile provider’s network. When you want to send a message, it goes first to the nearest cell tower before passing through the network, finally reaching your friend’s phone. As you move around, from home to school, for example, you will pass several towers. The closer you are to a tower the stronger the signal there, and the phone network uses this to estimate where you are, based on signal strength from several towers. This means that, as long as your phone is with you, it can act as a sensor for your location and track you, just like the Weasley’s whereabouts clock.

You could also have a similar system at home that monitors your location, so that it switches on the lights and heating as you get closer to home to welcome you back. On a typical day you might head home somewhere between 3 and 6pm (depending on after-school events) and as you leave school the connection to your phone from the tower nearest the school will weaken, but connections will strengthen with the other cell towers on your route home. But what if you appear to be heading home at 11 in the morning? Perhaps you are, or maybe actually the signal has just dropped from the tower nearest to the school so a tower nearer your home is now getting the strongest signal!

A system using Bayesian logic to determine ‘near home’ or ‘not near home’ can be trained to put things into context. Unless you are ill, it’s unlikely that you’d be heading home before the afternoon so you can use these predicted timings to give a likelihood score of an event (such as you heading home). A Bayesian network takes a piece of information (‘person might be nearby’) and considers this in the context of previous knowledge (‘and that’s expected at this time of day so probably true’ or ‘but is unlikely to be nearby now so more information is needed’). Unlike machine learning which just looks for any patterns in data, in a Bayesian networks approach the way one thing being considered does or does not cause other things is built in from the outset. Here it builds in the different possible causes of the signal dropping at a cell tower.

You could also set up a similar system in a home using wifi points to predict where you are and so what you are doing. Information like that could then feed data into a personalised artificial intelligence looking after you. Not all magic has to be run by magic!

-Jo Brodie, Queen Mary University of London, Spring 2021

Download Issue 27 of the cs4fn magazine on Smart Health here.

This post and issue 27 of the cs4fn magazine have been funded by EPSRC as part of the PAMBAYESIAN project. This article was inspired by

Inspired by the blog on Presence Detection Part 1: Home Assistant & Bayesian Probability and a previous cs4fn article on making a Whereabouts Clock.

Smart bags

In our stress-filled world with ever increasing levels of anxiety, it would be nice if technology could sometimes reduce stress rather than just add to it. That is the problem that QMUL’s Christine Farion set out to solve for her PhD. She wanted to do something stylish too, so she created a new kind of bag: a smart bag.

Christine realised that one thing that causes anxiety for a lot of people is forgetting everyday things. It is very common for us to forget keys, train tickets, passports and other everyday things we need for the day. Sometimes it’s just irritating. At other times it can ruin the day. Even when we don’t forget things, we waste time unpacking and repacking bags to make sure we really do have the things we need. Of course, the moment we unpack a bag to check, we increase the chance that something won’t be put back!

Electronic bags

Christine wondered if a smart bag could help. Over the space of several years, she built ten different prototypes using basic electronic kits, allowing her to explore lots of options. Her basic design has coloured lights on the outside of the bag, and a small scanner inside. To use the bag, you attach electronic tags to the things you don’t want to forget. They are like the ones shops use to keep track of stock and prevent shoplifting. Some tags are embedded into things like key fobs, while others can be stuck directly on to an object. Then when you pack your bag, you scan the objects with the reader as you put them in, and the lights show you they are definitely there. The different coloured lights allow you to create clear links – natural mappings – between the lights and the objects. For her own bag, Christine linked the blue light to a blue key fob with her keys, and the yellow light to her yellow hayfever tablet box.

In the wild

One of the strongest things about her work was she tested her bags extensively ‘in the wild’. She gave them to people who used them as part of their normal everyday life, asking them to report to her what did and didn’t work about them. This all fed in to the designs for subsequent bags and allowed her to learn what really mattered to make this kind of bag work for the people using it. One of the key things she discovered was that the technology needed to be completely simple to use. If it wasn’t both obvious how to use and quick and simple to do it wouldn’t be used.

Christine also used the bags herself, keeping a detailed diary of incidents related to the bags and their design. This is called ‘autoethnography’. She even used one bag as her own main bag for a year and a half, building it completely into her life, fixing problems as they arose. She took it to work, shopping, to coffee shops … wherever she went.

Suspicious?

When she had shown people her prototype bags, one of the common worries was that the electronics would look suspicious and be a problem when travelling. She set out to find out, taking her bag on journeys around the country, on trains and even to airports, travelling overseas on several occasions. There were no problems at all.

Fashion matters

As a bag is a personal item we carry around with us, it becomes part of our identity. She found that appropriate styling is, therefore, essential in this kind of wearable technology. There is no point making a smart bag that doesn’t fit the look that people want to carry around. This is a problem with a lot of today’s medical technology, for example. Objects that help with medical conditions: like diabetic monitors or drug pumps and even things as simple and useful as hearing aids or glasses, while ‘solving’ a problem, can lead to stigma if they look ugly. Fashion on the other hand does the opposite. It is all about being cool. Christine showed that by combining design of the technology with an understanding of fashion, her bags were seen as cool. Rather than designing just a single functional smart bag, ideally you need a range of bags, if the idea is to work for everyone.

Now, why don’t I have my glasses with me?

– Paul Curzon, Queen Mary University of London, Autumn 2018

Download Issue 25 of the cs4fn magazine “Technology Worn Out (and about) on Wearable Computing here.