Digital Signature

Trace of public bus movements and position in the city of Rome. Over time a pattern can be recognised and this creates a digital signature of public transport. Credit: Senseable Cities Lab MIT

A most sensitive accelerometer, able to detect 1/1000 of G acceleration. Hence the tiniest vibrations can be recorded. Credit: HP

In principle we can create a digital signature of everything, be it an object, a cluster of objects, a city, a “behaviour”. This digital signature characterizes the object and can be used to identify it and to detect anomalies in the object behaviour. 

 

A digital signature can become a Soft IoT once we encapsulate its values and associates rules to it. Here you have an example of using digital signatures created by analysing data from cell phones position. In a short while it is possibile to detect which phone happens to be on a public bus and from that create a digital signature of the bus (it is a dynamic one, since people are hopping on and off) and we can tell if the bus is running on schedule and if not we can work out the possibile reason (like: there is a traffic jam). Being a Soft IoT it can generate alerts letting people know that the bus is being delayed. Actually, the bus Soft IoT can change the context of people’s Soft IoT when they are interested by potential delay and they can take action accordingly.  All this happening in the cyberspace with no involvement of atoms.
Platforms like FIWare, also being considered by NIST for US smart cities, can support this Soft IoT communications.

Accelerometers are very good in creating digital signatures of objects analysing their vibrations. In the photo you see the Accelerometer developed by HP that can detect a variation of 1/1000 of G. That is an amazing sensitivity. If you place that sensor on a wall of your home and have a signal processing application analysing the data within a week the software can detect the presence in your home of a washing machine, three people living there and a cat. It can also tell the model of the washing machine and it can provide an alert when the door seal is worn down or the transmission belt is getting loose.

 

Again, the digital signature of the washing machine can be a Soft IoT we rely upon to tell us its status. Notice again the difference with the data provided by a single sensor. Here we have a significant processing going on that takes into account historical data and the context (vibrations are different depending on where the washing machine operates and local condition at that moment).  Additionally, the raw information on that model digital signature are provided on the web by the washing machine manufacturer. Our Soft IoT is an instance of the general Soft IoT created by the manufacturer.

Author - Roberto Saracco

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