the Human Hit Counter The Human Hit Counter translates to web stats for the physical world. It offers detailed traffic information not based on page hits but the number of people you detect via Bluetooth. The result is a unique representation of space displayed in a way as to highlight possible habitus routes and habitus route intersections. My project consists of a mobile phone application written in J2ME that logs Bluetooth users nearby and exports the data in an xml format. The second stage analysis, involves an application written in Processing. It reads the xml file created with the J2ME Application, and displays the data visually. I will offer instructions on how to collect data and analyse, a brief conclusion of the theory behind my practice and then downloads of the phone app and the processing source code and application. -- Step 1 : Collecting Data Download and install the application. Turn on Bluetooth, and load the application. Start the Logger by selecting 'start/stop BT Logger'. Commence Journey. At the end of your journey please stop the logger by selecting 'start/stop BT Logger' and then select ‘Save to file and exit’, this will write the contents of the memory to an .xml file. You will then need to transfer this file to your computer. To merge multiple journeys you will have to manually copy and paste the xml into a single theLog1.xml document. Step 2 : Analysing the Data. Place the theLog1.xml into the data folder and run the application, you then have three options. Home (green) Use this screen to browse by list and view large Time Charts. User (blue) Use this screen for a breakdown of an individual’s data into separate hours for each day. This is for comparison and features auto scaling. You can scroll through the Bluetooth Ids using the arrows bottom right. Time (red) This option is for viewing all users for a particular hour, you can scroll through the hours using the arrows bottom right. Time Chart The time charts are used to display all the information for a particular user at the same time. They are comparable and visible by user on both the ‘home screen’ and the ‘browse by user’ screen. The inner greyscale pie chart represents hours and the outer coloured pie chart represent the days. From this double chart you can easily deduce when you see a person most. For more detailed information please see the User breakdown screen (blue).
	Initial Research My initial ideals for this project were inspired by my dissertation. I am investigating applications of synesthesia and a lot of me early research focused on the senses. Albert Soesman identified twelve senses. He described 7 additional senses including sense of self movement. New Scientist now says there are over 20. Common but rough clarification is based on 5 physically visible senses. Models of our senses vary across cultures and species; I chose my spaceman because he had a special variation. The loggerhead turtle is born with the extra perceptual abilities to read the earths magnetic field. It is also equipped from birth with a built in representation of space for migration. Representations of Spaces Lefebvre uses what he calls “a conceptual triad” to explain the production of space. Representational spaces are the lived experiences that emerge as a result of the dialectical relation between spatial practice and representations of spaces. The turtle’s representation of space is in the form a magnetic migration map. He follows this to navigate throughout his life. How could I be influenced by the Loggerhead Turtle? For a full report of my early research please look here. I decided my extra sense would be Bluetooth; I would use it to construct a representation of space based on interaction. Every Bluetooth device has a unique hardware address, like the MAC address for computers. This will allow me to uniquely identify any one with a Bluetooth enabled device within 30 feet There have however been many attempts at Bluetooth spatial or proximity networks. They all need consumers to download the application and they all rely on you having the same client on every phone. ‘When is someone going to crack the ‘mobile social network via Bluetooth‘ conundrum?’  TechCrunch There two ways to crack this problem, one would be to develop software that could talk to every mobile spatial network available the other idea is to create one doesn't even require other mobile to have any specific software. I suggest a new social networking tool. One that relies on your personal collection of data not everyone else's. Log everything, Bluetooth and Time continuously reading and monitoring the data, creating a map of your social interactions over time. This will create a map of social interaction. Another application is for proximity alerts: In pubs or clubs, in a que, it even has potential for finding lost friends. If someone enters within 30 feet of you, you have the option be notified. Habitus The program reads through the data and sorts it by Mac Address and Time. The people featuring the most hits will then be displayed for comparison. The aim is to look for patterns. If there is a repeating or matching data this represents a habitual model.  Example if you walked to Babbage every Tuesday, this should be highlighted as a habitual route. 'Habitus is a complex concept conceived by Bourdieu, but in its simplest usage could be understood as a set of acquired patterns of thought, behaviour, and taste. These patterns or “dispositions” are the result of internalisation of culture or objective social structures through the experience of an individual or group. People do not simply obey rules in their everyday activities but form habits and acquire views through a complex process of experience and incremental judgements.' wikipedia With Habitus bourdieu explores the area Giddens discusses as ‘the routinisation of social action’. I am looking more specifically at the at the ‘the routinisation of social interaction’ If there is a repeating matching of data between you and someone else this represents a habitual route intersection. Knowing aspects of you own habitus model could be useful for... Monitor changes in your habits. Removing bad habits.   Knowing your own habitual route intersections could be useful for... Social networking Surveillance. Raise awareness of people you frequent the same time and space with. If you noticed that you always bumped into that hard to find lecture on Tuesday afternoons, then you would know where to find him.   Predicting the future? I have been influenced by my spaceman the loggerhead turtle to use an extra sense (Bluetooth) to construct and navigate a unique representation of space (habitual routes and interactions). Bourdieu says that habitus is continually reformed and modified by everyday experience and so will the capabilities of this tool. It’s all about collecting as much data as possible.
	Download Please click the processing icon below to download the source and application files. The log must be in the data folder and labelled theLog1.xml to work. You can view the applet online here.