Electropages: We need smart networks for tomorrow’s smarter cities

Electropages: We need smart networks for tomorrow’s smarter cities

And while you can’t necessarily use the same technology everywhere – geographical features, financial challenges, cultural considerations and technical issues all come into play when thinking about how to implement the smart city. What is clear is that the Internet of Things (IoT) will play a key role.

The IoT enables sensors and other connected devices to send data off for processing, either locally or in the cloud. The insights this results in can then be used to initiate appropriate actions. Using the IoT, you can connect every element in the city, from parking spaces to utility meters, to ultimately improve the way people, goods and utilities are moved around our urban areas.

Of course, connecting every street lamp, traffic light, energy meter, parking space, rubbish bin and more to the cloud – not to mention all the electrical appliances in every home and workplace – results in an enormous density of kit. And this raises big technical questions. How do you link all of these devices together in a way that’s energy-efficient, reliable and economically sustainable? What kind of network technology and topology do you need?

Mesh and capillary networks

Mesh networks are an obvious choice for smart cities. Instead of each device connecting directly to the cloud, nodes in the network connect to one another. Smart street lamps, for instance, linked using a mesh network, can exchange information about levels of ambient light in their immediate vicinity, or whether there are people or vehicles nearby. This will mean the network of lights can adjust itself dynamically, to improve safety and energy-efficiency.

Another approach is to use capillary networks. Here, a local mesh network connects to the cloud through some kind of gateway, usually via a low-bandwidth cellular technology. In our smart street lamp example, a capillary network could enable the local authority to remotely monitor the lighting network, visualise the data online and manually control the lights, if required.

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