IoT and OoT – Our View of Internet of Things

IoT and OoT – Our View of Internet of Things

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IoT – Everything Will Be Connected

“Data is a precious thing and will last longer than the systems themselves”

Tim Berners-Lee

IoT, or Internet of Things, or as commonly recognised IoT, is the network of physical “objects” embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data. The galaxy of solutions that we are going to approach in the next future will be somehow related to the world of interconnections between humans and smart objects.

Our future will even more a conjunction between our actions and our digital devices. It should be clear that IoT will cover many different application fields, development cycles and technologies. Thus, implementing vertical solutions to cover any aspect could be really difficult.

Within this approach that any Digital Devices “DiDe” will produce info to be collected, we can also call the IoT as Input of Things.

Furthermore, this amount of data will be collected, stored, and aggregated in order to produce, somehow, an “Output of Things” or as we call it, OoT

Basically, the flow of data will be something like IoT to OoT and nowadays there is a big attention into this last one, but maybe not in the right way…

We consider that the most important point about this huge amount of collected data will be the Output, rightly aggregated and correlated to produce “something” that will create humans action:

    1. Just think, as example, about an automotive application. Consider a car with many sensor that control parameters from car about stability: positioning on the road, distances between obstacle, height between car and ground, and so on… In this way, an example of output could be bother an automatic correction of car direction or an alarm to the driver to change his way to drive.
    2. Another example, about MNO, could be on the use of the SON and CEM. In the next future, using the new upcoming technologies, a Mobile Network will be able to become a “Macro Automatic System” (MAS) that will adapt itself to satisfy customer needs and repair itself as well. Of course some human action will be always a need but the system itself could be able to “communicate” directly with the right engineers to ask for an help.

Huge Amount of Data

Thinking about above points, it should clear that the amount of data collected, and transmitted within the network, will grow exponentially to become huge!

“In general, most telecom providers have seen data growth of 40-50% year over year. Popular business logic would presume a proportional reduction in the total cost of network ownership to deliver this data profitably. In truth, this is somewhat of a misleading and simplified statement.

The cost to deliver a GB of data can be roughly calculated by dividing the sum of the depreciated capital expenditure and operational expenditure by the total GBs produced by the network. This implies that the cost per GB declines as the utilisation of the network increases (more data consumption actually decreases the cost).

Furthermore, within a given cellular generation, the rise in operational costs for capacity upgrades is generally marginal. Obviously, the network will eventually saturate (approximately 70% utilisation, depending on the number of cell sites and spectrum assets the service provider owns) and a more spectrally efficient technology will need to be deployed to upgrade the network (such as LTE-Advanced Pro, and the much anticipated 5G).”

Ref.  Rethinking Telecom Next 10 Years
Vish Nandlall – Accomplished CTO, IoT Industrialist & Big Data Strategist

Use a BIG DATA infrastructure will become a must for any company that will offer some services based on IoT.

In this way, potentially any company can start to pull together increasing data volumes for analytics, correlation, alarms, or simply to store for undetermined future use. Of course, one of the most important point about data analysis is, as always, the algorithms to process the data. Anyone that will be able to produce quick and reliable algorithm, potentially will have something to use within any application.

From the moment that many giant are already working into the architectures of IoT, we concentrate our effort to produce reliable algorithms.

    • Collection
    • Processing & Analytics
    • Presentation

Our Point of View

Broadly, the presentation layer can be exploded in many ways and what we are working on is an “ALARMS Layer”

Our opinion is that at the first stage of IoT provisioning, many applications will need to quickly react to trigger or alarms, generated by DiDe’s data. In fact, the conjunction between humans and DiDe will become a new Customer Experience measured by the user’s feeling about control of his DiDe itself.

Soon we will have many wearables and others DiDe that will try to communicate, in some ways, with his user. If this will be comfortable about the quickness of any reaction than the CE will be good otherwise will not…

Our approach to optimise this DiDe CE is to have a system that could aggregate and correlate all these information and generate push messages.

We are already working on a special project for MNO about alarms on Signal Coverage Levels, Drop Call Rate, Data Throughput DL/UL, and many more. Collected data are originated by Mobile APP (Customer Probes), Network Probes and OSS/BSS info. Basically the cross correlation of all these info will be done by our system that will generate push messages to a dedicated APP that will, as well, generate a “picture” of the situation based on the boundaries condition recorded.

Obviously, all the information can, and should, be GEO-Located based on the GPS information collected.

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