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La fioritura di una varietà di Apps di contact tracing tese a contrastare la pandemia ha acceso discussioni sulla loro efficacia, sull’affidabilità della tecnologia su cui si basano, sulla raccolta e sull’utilizzo dei dati e sulla loro conformità con le norme in materia di Privacy.

Se rintracciare i positivi al Covid-19 attraverso il dispositivo più diffuso tra i cittadini di tutte le età e le classi sociali, ovvero lo smartphone, potrebbe sembrare efficace, le difficoltà da superare non mancano. Si pensi ad esempio alla capacità di effettuare su larga scala i test medici, senza i quali non potremmo accertare chi sia effettivamente portatore del virus. …


Governments are faced by a choice between data surveillance or data democratization

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The Covid-19 epidemic is threatening not just our health systems but the entire world economy. Strong and immediate measures are needed to limit contagion, save the highest number of human lives and limit the economic consequences, but every decision that our Institutions will take in this time of emergency will inevitably affect our future. Therefore it is necessary to immediately identify the impact that current choices will have on citizens and nations’ future.

Why do we need a massive use of citizens’ personal data?

The need of limiting infection through restrictive behavior rules has proven that availability of real-time citizens’ personal data is fundamental. The availability of ‘Big Data’ streaming from connected things, such as smartphones or wearables, provides real time visibility over the status of a phenomenon and the possibility to predict its changes in the short term, thus supporting timely and informed decisions. …


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HOW BIG IS BIG DATA?

Well, one single energy meter generates 1 million data points per day. This means that about 20 energy meters would generate as much data as 20,000 Walmart stores.

Let’s start by discussing how big is Big Data. For example, Walmart customer transactions generate about 1 million data points per hour. Big, isn’t it?

WHAT DO WE NEED ALL THIS DATA FOR?

Basically, IoT Big Data can enable you to do two things:

  • To discover something that we do not expect
  • To respond to something that we do expect

You just need to treat the same data differently to achieve these different goals.

In order to discover unknown data patterns and correlations you need past data, or data sets, while to provide instant responsiveness you need live data, or data streams. …


In cities there will be 75 Billion of connected IoT devices by 2030. The availability of IoT real time data through data exchange hubs holds the promise of making our cities smarter, safer, cleaner and more efficient. These are objectives we all share as citizens — but we do not want to give up control over our personal data to achieve them.

The question then is — how can IoT and Data Privacy be reconciled?

Blockchain and Data Access Control

The unexpected answer is — with Blockchain. Blockchain will empower citizens to control access to their IoT live data, significantly increasing their trust & willingness to collaborate in making cities a better place to live. …


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Where is the real money in IIoT?

Industrial IoT (IIoT) is a huge business opportunity. According to IndustryARC research (June 2016), the IIoT market is estimated to reach $123.89 Billion by 2021 at a high CAGR. According to Accenture, the impact of IIoT on global GDP will be $14.3 Trillion by 2030.

Up to 60% of this value is in the transformational opportunities offered by IIoT to create new collaborative business models, involving all value chain stakeholders, and in developing new revenue streams.

However, the core focus of most Industrial Internet of Things deployments and of the majority of organizations is still on operational efficiency, along with cost optimization. Or, as IDC described it, efficiency optimization and linking islands of automation are still key IIoT drivers.


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The IoT will give rise to the IoD — the Internet of (very Big) Data. The business opportunity is big too, but what about the costs?

How Big is Big Data?

Let’s start by discussing how big is Big Data. For example, Walmart customer transactions generate about 1 million data points per hour. Big, isn’t it?
Well, one single energy meter generates 1 million data points per day. This means that about 20 energy meters would generate as much data as 20,000 Walmart stores.

Big Data = Big Money?

If this sounds scary, it’s because you are thinking that big data equals big data storage — and consequently big money. And you’d be right, since this is what we have always been doing with data generated by human activities — store data first, use it later. …

Ecosteer

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