Antwerpen wordt een hyperintelligente ‘City of Things’
_{8 mei 2015}

1. GPS tracks your location.
2. Proximity Sensor turns the screen off when you hold it to your face.
3. Ambient Light Sensor automatically adjusts brightness.
4. Accelerometer senses movement and orientation.
5. Barometer measures pressure.
6. Temperature Sensor measures the temperature.
7. Humidity Sensor measures the humidity.
8. Magnetic Sensor measures the magnetic field.
9. Gesture Sensor senses your hands to navigate.
10. Infrared Sensor turns the phone into a remote control.
11. Eye Tracker pauses video when you look away.
12. NFC (Near Field Communication) shares data by touching two phones and also enables mobile payments.
13. Dual Cameras are available; one on the front and one on the back of the phone. Both cameras can record simultaneously in the Samsung Galaxy S6.
14. Dual Microphones are used in the phone; one microphone for voice and the other to listen to the ambient noise and create anti-noise using the noise-cancelling system.

So far, phones usually had a CPU with a single core. With the launch of Samsung Galaxy S6, we are entering a new era of smartphone computing. The Samsung Galaxy S6 has an Octa-core processor (8 cores). Why does a smartphone need so much power? When a home computer can do everything with a slower processor (and single core), why does a smartphone need a faster processor (with 8 cores)? The Samsung Galaxy S6 has the following components that a home computer or even a basic business computer does not have: _{[de 14 sensoren, zie hierboven]} These sensors constantly gather large amounts of data and need constant processing. A CPU must have multiple cores to compute all this data simultaneously. The CPU assigns tasks to different cores, keeping a single core from overheating. Less heat is generated and hence, less power is consumed. With battery technology not evolving as fast as CPUs, manufacturers don’t have a choice but to make CPUs that are more efficient in terms of power consumption and heat emission. BRON _{15 mrt 2015}

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Internet Of Things: New Architecture Needed
_{26 jun 2014}

Big Data and IoT Lambda Architecture
_{7 nov 2016}

Lambda architecture
is a data-processing architecture
designed to handle massive quantities of data
by taking advantage of both
batch- and stream-processing methods.

• is lage latency vereist,
• er wordt gewerkt met bijvoorbeeld Apache Storm,
• en de output verdwijnt in een NoSQL database

• beheert de master dataset,
• er wordt gewerkt met bijvoorbeeld Apache Hadoop,
• en de output verdwijnt in read-only database

• wordt de output van beide voorgaande lagen bediend
• voor queries uit te voeren
• de output wordt gestockeerd op bijvoorbeeld Apache Hbase

Lambda Architecture: Low Latency Data in a Batch Processing World
_{28 sep 2015}

Questioning the Lambda Architecture
_{Jay Kreps
2 jul 2014}

Kappa Architecture is a simplification of Lambda Architecture.
A Kappa Architecture system is like a Lambda Architecture system
with the batch processing system removed. To replace batch processing,
data is simply fed through the streaming system quickly.
BRON

Running at Google Scale With the Zeta Architecture
_{19 mei 2015}

1. Distributed File System:
   Utilizing a shared distributed file system,
   all applications will be able to read and write
   to a common location which enables
   simplification of the rest of the architecture.
2. Real-time Data Storage:
   This supports the need for
   high-speed business applications
   through the use of real-time databases.
3. Pluggable Compute Model / Execution Engine:
   Different groups within a business
   have different needs and requirements
   for meeting the demands put upon them
   at any given time, which requires the support
   of potentially different engines and models
   to meet the needs of the business.
4. Deployment / Container Management System:
   The need for having a standardized approach
   for deploying software are important
   and all resource consumers
   should be able to be isolated and deployed
   in a standard way.
5. Solution Architecture:
   This focuses on solving a particular business problem.
   There may be one or more applications built
   to deliver the complete solution.
   These solution architectures generally encompass
   a higher level interaction
   amongst common algorithms or libraries,
   software components and business workflows.
   All too often solution architectures
   are folded into enterprise architectures,
   but there is a clear separation with the Zeta Architecture.
6. Enterprise Applications:
   In the past these applications
   would drive the rest of the architecture.
   However, in this new model there is a shift.
   The rest of the architecture
   now simplifies these applications
   by delivering the components necessary
   to realize all of the business goals
   we are defining for this architecture.
7. Dynamic and Global Resource Management:
   Allows dynamic allocation of resources
   to enable the business
   to easily accommodate
   for whatever task
   is the most important today.

The location of the components in the hexagon were chosen with good reason as well.
The distributed file system sits at the bottom as everything is built on top it.

The compute model / execution engine and the real-time data storage are effectively
married to the distributed file system
as that is where the data will reside whether the data is moving in, or out.

The enterprise applications were placed sitting on top of the solution architecture
and the deployment / container management system
because they are the support for the enterprise applications
and define how the enterprise applications will work.

Lastly, the resource management touches everything
and thusly sits in the center of the diagram.