Latest news:
Sub story to regular feature: Issue 595 27 Apr 2012

Smart cities and the Internet of Things (IoT): a real game-changer

In addition to connecting people, the internet increasingly connects things. In its recent report, Machine to Machine (M2M) communication: Connecting billions of devices, the Organisation for Economic Co-operation and Development (OECD) analyses the impact of this phenomenon and outlines ways in which IoT will impact on transport, energy, built environment and telecoms providers – a debate that will be continued at Modelling World

By 2017, an OECD average family with two teenagers could have as many as 25 'things' connected to the internet: telephones, TV, tablets, in-car devices, energy meters, printers and health devices. The combination of data from this plethora of sources will support the development of truly smart cities: smart transport, smart energy and smart health.

The OECD's Rudolf Van Der Berg suggests that telecomms liberalisation could become an essential element of sound transport policy, riding on the back of a regulatory revolution in which data privacy, one-country roaming policies and restrictive mobile business models are a thing of the past. New types of network, and new network users, will emerge as Machine to Machine (M2M) communication becomes standard, suggests Van Der Berg. Governments are considering enabling large-scale M2M users to own their own SIM-cards, making a car manufacturer equal to a mobile operator from a network perspective. Current policy suggests that from 2015, the European Union is making plans that will see (networks permitting)  a percentage of vehicles featuring eCall (a European initiative intended to bring rapid assistance to motorists involved in a collision, via a device that will automatically dial 112 in the event of a serious road accident, and wirelessly send airbag deployment and impact sensor information, as well as GPS coordinates, to local emergency agencies).

Usman Haque is the developer of Pachube, a convenient, secure and scalable platform that is helping us connect to and create the Internet of Things.  We at Modelling World have been keeping an eye on these developments, and plan to showcase some of the most interesting case studies at the event. As a generalised real-time data brokerage platform, Pachube's key aim is to facilitate interaction between remote environments, both physical and virtual. Along with enabling direct connections between any two responsive environments, Pachube can also facilitate many-to-many connections. But the emphasis is less about the data gathered and more about the possibilities offered by the process of collecting data. Sharing, interoperability, and collaboration are key. For developers and service providers, a 'layered' open Internet of Things brings with it the opportunity to innovate on top of existing data, says Haque. Users will bring that data with them and developers will be able to focus on the rich possibilities of how to leverage data.

Many projects are already underway using sensors to collect data. Last year, four companies came together to explore how sensors can work with city parking, a major challenge for urban dwellers, city managers and planners.

Pachube, Worldsensing, Cisco and AT& T collaborated on a pilot project using the IPv6 protocol to connect sensors that report the availability of parking spaces to citizens and city management officials in a major European city. Sensors from Worldsensing send the data to a Pachube platform, and AT&T provides redundant IPv6 Internet services to both companies. Cisco is providing networking equipment to enable this showcase. Citizens have access to 24-7 data about available parking spaces. In addition, it provides city management with information about parking space usage. The information from the parking sensor data in this showcase is stored in Pachube’s cloud.

From a transport modelling perspective, the most exciting aspect is that IoT may change travel behaviour to an extent that extrapolating currently observed patterns and values would be very wrong; and how to use the data to improve our understanding and representation of such future behaviour.


Add a comment