‘Bintel’ is an
innovative urban waste management system that aims to improve the liveability,
attractiveness, efficiency, and environmental management of the city and its
services. Developed in line with a re-imagination of urban areas’ pre-existing
infrastructure, ‘Bintel’ provides potential administrations with an opportunity
to increase their influence throughout the city more efficiently and
cost-effectively through the use of low-cost sensors.
Re-invigorating one of urban administrations most
resource-intensive initiatives, ‘Bintel’ aims to provide decision makers with
context and location specific information in real time analysis of city life. ‘Bintel’
is another component of an increasingly wider constellation of instrumented
devices, often developed under the remit of the wider smart city agenda. The embedding
of low cost sensors into previously ‘unconnected’ devices aims to provide
councils with additional sources of big data. Utilising both the hardware and
software provided by both Intel and IBM at this event, this service provides
prospective councils with an opportunity to govern in a dynamic manner while simultaneously
seeks to make cities cleaner, safer, efficient, and more connected. By alerting
prospective councils’ attention to imminent environmental and infrastructural
concerns this form of technology aims to optimise the management of waste
collection routes. Moreover, this managerial optimisation seeks to reduce both
fuel and labour costs along more environmentally supportive rationales.
Accordingly, this data may be correlated with the city’s various other datasets
in order to create a more contextually contingent visualisation of the city
from a wider sociotechnical perspective.
The primary aim of ‘Bintel’ is to address existing issues by
retrofitting already existing mediums like the vast array of bins that are
dotted around the city’s various neighbourhoods. In the digitally enhanced
streetscapes of modern cities this initiative seeks to provide self-powered,
energy efficient, ubiquitous, and low cost sensors in comparison to
contemporary private models whose pricing plans differ dramatically.
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