Introduction

Transferring, storing and processing of various multimedia data while being mobile, moving from one location to another using mobile internet devices (smartphone) that are connected to diverse wireless networks and cellular mobile technologies

1. Data to Intelligence: extracting and embedding, individual, group or community - BIG DATA AI

2. Mobility: AnyDevice, AnyNetwork, AnyWhere, AnyTime, AnyPlace (AnyX phenomenon)

3. Mobile Edge Computing (MEC): Intelligence and computation are now pushed to the edge devices

• IoNT: Internet of Nano Things (underlying nanoscale networks connecting a multitude of nano sensors)

• IIoT: Industrial Internet of Things (application in the industry)

• IoE: Internet of Everything (including humans)

CPS refers to the integration of computation and physical processes (such as sensors, people and physical environments) via a communication network In

Some devices are technology related i. e. developed based upon standards they operate.

Devices can have multiple modules to support several standards.

• Smartphones

• Internt of Things or sensors

• Wearable Computers

• Cloud

• Fog & Edge Computing

The Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks.

• Enhanced Mobile Broadband (EMBB)

• Ultra-Reliable Low Latency Communications (uRLLC)

• Massive Machine Type Communications (mMTC)

• Delay or Latency - additive behavior

• Bandwidth or Capacity- concave or convex behavior

• Loss - multiplicative

• Cost/Price - additive behavior

• Hop count - additive behavior

• guaranteeing stringent latency is a more important service requirements for many applications

  • e. g. Tactile Internet applications, vehicular safety, haptic communications have delay requirements between 1 ms to 10 ms (total delay)

Devices are not yet efficient enough regarding communication, storage and processing.

When used in these scenarios, they heat up, loose efficiency and degrade the battery.

So a market demand is needed for more efficient sensors to achieve a breakthrough.

• Their objective is to achieve lower latencies by pushing intelligence to the edge of the network.

• Edge and/or Fog computing devices generally will have some computing, storage and communication services built in the devices.

• Their difference is, that fog computing adds an intermediary layer of fog nodes between edge devices and the centralized cloud.

• Application use cases

• Choice of sensor hardware

• Types of data to be collected

• Real-time or non-real-time or hybrid

• Network

• Radio environments

• Location of sensor placements

1.       Cybersecurity

2.       Lack of Standardization

3.       Legacy-installed base

4.       Significant upfront investments

5.       Lack of skilled workers

6.       Data integrity

7.       Internal system barriers

8.       Liability of current technologies

9.       Social/political concerns

• Efficiency: better use of time speeds up process

• Safety: People exposed to less hazardous environments

• Society: Monitoring for health and social care

• Environment: Pollution levels, air quality, flooding alerts

• Innovation: New products and service opportunities or new markets

• Business intelligence: Allowing gathering of data to make better decisions to benefit organizations.

• Compliance: New and more effective ways to monitor and report compliance requirements

• Profitability: Cost savings and increased productivity leads to increased profitability

• Productivity: Identify and eliminate errors

Vince: SPEI