Public Open Sensor Data: Revolutionizing Smart Cities
T&S Paper by Albert Domingo, Boris Bellalta, Manuel Palacin, Miquel Oliver, and Esteve Almirall; Winter 2013
Abstract: Local governments have decided to take advantage of the presence of wireless sensor networks (WSNs) in their cities to efficiently manage several applications in their daily responsibilities. The enormous amount of information collected by sensor devices allows the automation of several real-time services to improve city management by using intelligent traffic-light patterns during rush hour, reducing water consumption in parks, or efficiently routing garbage collection trucks throughout the city . The sensor information required by these examples is mostly self-consumed by city-designed applications and managers.
Comparing British and Japanese Perceptions of a Wearable Ubiquitous Monitoring Device
T&S Paper by Stuart Moran, Toyoaki Nishida, and Keiichi Nakata Winter 2013
Mixed Reality Lab., Univ. Nottingham, Nottingham, UK
Abstract: Ubiquitous Monitoring (UM) describes the continuous collection of data on a large scale, enabled by embedded, mobile, wireless, and sensory technologies. This data will enable the envisioned applications of Ubiquitous Computing. Research has shown that monitoring can affect user behavior , which is problematic for ubiquitous computing because the data collected may not fully reflect the reality. Hence, any services provided may not fully align with user expectations or needs. One proposed solution is the use of deterministic models to predict the behaviors of users prior to deployment, reducing the undesirable effects of monitoring. The Perceptions of System Attributes-Behavioral Intention (PSA-BI) model was specifically designed for this purpose . While the model has been validated, the moderating effect of culture has not yet been explored. As such, we present here results from a study carried out in the U.K. exploring the relationships in the PSA-BI model. This is then compared with a structural model from a previous study in Japan, allowing us to explore any potential differences and similarities.
Asynchronous Adaptations to Complex Social Interactions*
T&S Paper by Sally Applin and Michael Fischer Winter 2013
Centre for Social Anthropology & Comput., Univ. of Kent, Canterbury, UK
Abstract: The permeation of the mobile platform is creating a shift in community behavior. What began with a few individuals, has now quickly replicated as many people communicate not only through mobile phones, but through smartphones that are multi-functioning communications computers. Mobile devices have broadened people’s capability and reach, and within that context, people have adapted their behavior to adjust to communications “on the go.” In this article we explore how multiplexed networked individuated communications are creating new contexts for human behavior within communities, particularly noting the shift from synchronous to asynchronous communication as an adaptation.
A Wall Street Journal (WSJ) article on March 7th outlines how employers are using sensors in the workplace to track employees. An example is Bank of America (BoA) which asked some of their call center employees to wear ID badges with sensors tracking location and tone of conversations. The objective was to learn how F2F (face to face) time with co-workers might improve effectiveness. (Indications are that switching employees to common break times increased productivity by 10%)
According to the article, research indicates that increases in time “in the cubicle” might indicate an employee is more likely to leave their job in the next few months. Similarly increases in interactions with co-workers seems to be a predictor of folks likely to get promoted. (Compare with the recent Yahoo policy reducing or eliminating telecommuting)
RFID chips in employee badges allow easy entry controls, and can be combined with bio-metrics for secure environments But of course can also be used to track employee activity within the facilities. Employers have the right to monitor and archive online activity using corporate systems and networks (in the U.S.)
And more sophisticated monitoring is emerging as indicated by the BoA use of “tone of conversation” as a factor. Presumably other sensor aspects could be incorporated and tracked. Stress tracking, implicit lie detection, rates of motion, who knows?
Results of some of this research has lead to common break times, larger lunch tables, fewer coffee stations — in essence encouraging folks to interact in the workplace.
There may be other results that are not covered by the WSJ article. What do you do if someone’s activities might correlate with increased likelihood of leaving the job? Is there liability for the employer if indications exist of possible disease (slower movement, more bathroom breaks, not going to lunch, etc.) And of course what risks are there for employees with a much closer monitoring of their activities?
How would you feel about this in your company?
Is this acceptable in your country and/or culture?