os desafios da internet das coisas - the iot challengesfredy/seminario-iot.pdf · the iot...

The IoT Challenges – 27/04/2016

Os Desafios da Internet das Coisas -The IoT Challenges

P RO F. D R . F R E DY J OÃ O VA L E N T E - 2 7 / 0 4 / 2 0 1 6


Agenda

• Definitions of IoT

• Market forecast

• IoT Technology Enablers• Devices, Communication, Protocols, Architecture, Security, Databases

• IoT RoadMap

• Future Internet• Design

• Digital Economy

• Tech trends

• Applications• New tech Developments

• Research Needs


IoT - Definitions

Shancang Li & Li Da Xu & Shanshan Zhao, “The internet of things: a survey”, Faculty of Engineering, University of Bristol, Department of Information Technology and Decision Science, Old Dominion University, Norfolk, VA 23529, USA, School of Computing, University of the West of Scotland, April 2014

“The capacity of sensing the environment through a population of objects in that environment becamesynonym to pervasive computing. The sensor network is the main enabler of IoT which intermitentlysample-compute-actuate.”

Arkady Zaslavsky, Charith Perera, Dimitrios Georgakopoulos, “Sensing as a Service & Big Data”, ICT Centre, CSIRO, Canberra, ACT, 2601, Australia, Research School of Computer Science, The Australian National University, Canberra, ACT 0200, Australia, published at Cornell University Library, 2013.

“The Internet of Things is a system where the Internet is connected to the real world via ubiquitous sensors”

Kevin Ashton, "That 'Internet of Things' Thing", RFID Journal, 22 June 2009 – co-founder of MIT Auto ID Center which developed EPC/UHF RFID

“IoT is a global dynamic network infrastructure capable of auto-configuration based around standardised interoperable communication protocols. Physical and virtual ´things´ have identities and atributes which are capable of utilising inteligent interfaces and be integrated to na information network”.

http://www.rfidjournal.com/article/view/4986


IoT Market Forecast 2020Annual groth rate 16.9% (devices, connectivity & TI services) – from $655.8 billion 2014 to $1.7 trillion in 2020

◦ Intelligent lighting, HVAC, smart buildings – to reach $200 Bn by 2020,

◦ Vertical specific devices such as smart surgery rooms, smart agriculture, container tracking, ships, airplanes, etc – to reach $667 Bn by 2020.

◦ In general, value generation will be provided by IT services & solutions, BigData & Analytics enabling the d-Business age.

Source: Gartner / IDC


Internet of Things: The story so far

RFID based

solutions

Wireless Sensor and

Actuator networks

, solutions for

communication

technologies, energy

efficiency, routing, …

Smart Devices/

Web-enabled Apps/Services,

initial products,

vertical applications, early

concepts and demos, …

Physical-Cyber-Social Systems, Linked-

data, semantics,

More products, more heterogeneity,

solutions for control and monitoring,

…

Future: Cloud, Big (IoT) Data Analytics,

Interoperability, Enhanced

Cellular/Wireless Com. for IoT, Real-

world operational use-cases and

Industry and B2B services/applications,

more Standards…

Motion sensor

Motion sensor

ECG sensor

P. Barnaghi, A. Sheth, "Internet of Things: the story so far", IEEE IoT Newsletter, September 2014.


IoT – Enabling technologies

• Embedded devices: RFID or wireless sensor networks (WSN), may be part of the IoT - but as stand alone

applications (intranets) they miss the back-end information infrastructures necessary to create newservices. The

IoT has come to mean much more that just networked RFID systems. RFID systems are standardized - WSN still

lacks that !

• Applications: IoT applications need to explore the infrastructure in full – small applications cannot be referred as

IoT without real impact on a global Internet.

• Ubiquitous/pervasive computing: Although

small computing devices and the ubiquitous

services derived from their data is probably a

requirement for the IoT, pervasive computing is

NOT the IoT.

• The Internet Protocol: Widely used globally for

clients and servers, however many objects in

the IoT will not be able to run an Internet

Protocol.

• Communication technologies: Very important

part in the IoT. There is a myriad of emerging

wireless communication such as WiFi,

Bluetooth, ZigBee, 6LoWPAN, LTE, LoRa

available to the IoT.

Ref: Internet of Things Strategic Research Roadmap, IfM – University of Cambridge


HW – Sensor Devices: widely available

Ready to use sensors:• Humidity, Temperature (air/soil/water), humidity on leaves, Ph, Calcium, Nitrate, Wind Speed, Atmospheric

pressure, solar radiation, pluviometre, stem diametre, luminosity, watering, reservoir levels, liquid flux, gas flux etc

Source: libelium.com


Wireless Communication for IoT

6LoWPAN / Mobile

Standard: BLE 4.22.4GhzRange: up to 150m1Mbps

Mesh / IndustrialStandard: IEEE802.15.42.4GhzRange: up to 100m250kbps

Mesh / HomeStandard:Z-Wave Alliance ZAD12837 / ITU-T G.995900 MhzRange: up to 30m100kbps

6LoWPAN

Standard: RFC6282 / spec IPv6 / TCP /MQTT / CoAP900 Mhz / 2.4 Ghz etcRange: N/AN/A

Mesh / Home / MobileStandard: IEEE802.15.4 / 6LoWPAN2.4 Ghz MhzRange: N/AN/A

Standard: IEEE802.11n2.4/5GhzRange: up to 50mUp to 1Gbit/s

Mobile / Celular

Standard: GPRS/UMTS-HSPA/LTE900/1800/1900/2100 MhzRange: avg 30km / 200km for HSPA35kbps-10Mbps

Ticketing / authenticationTwo way secure communication – AESStandard: ISO/IEC 18000-3C13,56 MhzRange: 10cm 10-420kbps

WAN / M2MStandard:SigfoxUHF 900 MhzRange: 30-50km10-1000bps

WAN / M2MStandard:NeulUHF 900/458/470-490 Mhz Range: 10km10-100 kbps

WAN / M2MStandard:LoRavarious Range: 15-20km0,3-50kbps

Secure Supply ChainTwo way secure communication v2 – AESStandard: ISO/IEC 18000-63915 MhzRange: 7m / anti-collision up tp 600 tags/s115,2kbps


IoT – communication protocols

MQTT (formerly Message Queue Telemetry Transport) is an ISO standard (ISO/IEC PRF 20922) Client Server publish-subscribe based "light weight" messaging protocol for use on top of the TCP/IP (MQTT-S runs on top of UDP) for constrained environments such as M2M and IoT:

◦ MQTT brokers available: ActiveMQ, Apollo, HiveMQ, IBM Message Sight, JoramMQ, Mosquitto, RabbitMQ, Solace Message Routers, and VerneMQ

CoAP (Constrained Application Protocol) - intended to be used in very simple electronics devices such as low power sensors (M2M and IoT) – it is Web Services oriented. Runs on top of UDP. See RFC 7252. Already implemented in most programming languages.

REST API, XMPP


Middleware / Architecture

•Kaa: Middleware IoT: permite a interconexão de sensores e

dispositivos e Aplicações

•Permite múltiplos canais de comunicação e diversas

tecnologias (WiFi, zigbee, LoRa, 4G/LTE, RFID etc);

•Roda em núvem: permite conectividade (dispositivo/núvem)

fim-a-fim e segurança fim-a-fim;

•Permite o inventário ativo de dispositivos, captura as

especificações de cada dispositivo, distribui atualizações de

firmware;

•Suporta MQTT e CoAP (M2M);

•Suporta BigData (NoSQL - mongoDB, Hadoop, Cassandra)•Suporta (virtualmente) qualquer hardware desde low-power

MCU´s (LoRa, LTE cat 0)) até Windows, Linux, Ubuntu, Apple,RaspberryPi, STM (ARM), Intel, RTOS (RFID), Android e iOS;

•Pode manusear milhões de dispositivos conectados – emúltiplos servidores / Aplicações, Integração via REST API

•Modelo de dados estruturado, não estruturado, compatívelcom Apache Avro e GUI para schemas de dados


Security Issues in IoT – big challenge

•To secure IoT, we must define the IoT

•Unprotected devices on theInternet will be attacked

•Encryption is neededthroughout the data lifecycle

•** implement security alreadydeployed in NFC / RFID intomotes: tough ! ** sugestion

•Single security model for all IoT communications

•Data stream access controls

•Tracking device metadata

•Secure provisioning in the field

•Firmware updates in the field

•Compliance with global regulations

•Leaving security up to each IoT project team


Ten

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Internet of Things

Machine-to-Machine

Isolated (autonomous, disconnected)

Monitored

Smart Systems

(Intelligence in Subnets of Things )

Telemetry andTelematics

Smart HomesConnected Cars

Intelligent BuildingsIntelligent Transport

SystemsSmart Meters and Grids

Smart RetailingSmart Enterprise

Management

Remotely controlled and managed

Building automation

ManufacturingSecurityUtilities

Internet of Things

Sensors

Devices

Systems

Things

Processes

People

Industries

Products

Services

Growth in connections generates an unparalleled scale of data

Source: Machina Research 2014

The Need for Big Data


Data Lifecycle - challenge

Source: The IET Technical Report, Digital Technology Adoption in the Smart Built Environment: Challenges and opportunities of data driven systems for building, community and city-scale applications,http://www.theiet.org/sectors/built-environment/resources/digital-technology.cfm

“Data will come from various source and from different platforms and various systems.”

This requires an ecosystem of IoT systems with several backend support components (e.g. pub/sub, storage, discovery, and access services). Semantic interoperability is also a key requirement.


IoT : ex. Remote Condition Monitoring

Vehicle Equipped with telematics unit

Sensors to monitor moving parts,

hydraulics liquids, etc

Partners Service provider

Repair specialist and vehicle

manufacturers

Vehicle Driver On-board diagnostics

Information about other vehicles, e.g. to

unload harvest

Vehicle Operations Intelligent monitoring of machine KPIs

and fluid analysis

Optimum servicing intervals

IoT


ScalabilityHeterogeneity

Agility & Flexibility

inApplications, Devices

and Connectivity

ScalabilityFlexibilityAnalytics

Unified View

inData

M2M & IoT Application Platforms

Data Databases

SQL(Oracle, IBM, etc.)for structured data

Hybrid(SAP Hana, VoltDB, etc.)

for speed and heterogeneity

NoSQL(MongoDB, Cassandra, etc.)for agility and heterogeneity

Source: Machina Research 2014

IoT-Platforms and Database-Systems


Technology Roadmap for IoT


The Industrialisation of Message Generation


IoT – 6A Conectivity

The Internet of Things could allow people and things to be connected Anytime, Anyplace, with Anything and Anyone, ideally using Any path/network and Any service.

“From anytime, anyplace connectivity for anyone, we will now have connectivity for anything” (ITU)


Smart object dimensions:

• Smart objects are able to sense, interpret, and react to external such as:• Convergence, Content, Collections (Repositories), Computing, Communication, and Connectivity

allowing seamless interconnection between people and things and/or between things and things.

•The IoT could imply a symbiotic interaction between the real/physical, world, and the digital/virtual world: physical entities have digital counterparts and virtual representation; • things become context aware and they can sense, communicate, interact, exchange data,

information and knowledge.

Activity-aware objects, policy-aware objects, and process-aware objects.

• Three design dimensions to use in the design of “Internet of smart objects.”


Future Internet

• Future Internet considers thefusion of IoT, IoP, IoE, IoM and IoSin a global IT platforminterconnecting intelligent thingsand objects.

• IoP (Internet of People) will interconnect people maintaining their control over online activities in organisations, communities –information producers and consumers (“prosumers”).

• IoE (Internet of Energy) – dynamic infrastructure connecting energy with the Internet – for generationand distribution of energy packets where and when necessary.

• IoS (Internet of Services) denotes a network which will deliver service componentes through the Internet enabling SOA, Web/enterprise 3.0/X.0, Interoperability among enterprises, Web Services, GRID and Semantic Web between consumers and producers.

• IoM (Internet of Media) will address the challenges of coding and processing of scalable vídeo for multi players in gaming environments, digital cinema and virtual worlds which will demand new strategies for data traffic and mobile architectures.


Object connected to Internet of Things and their three main challenging domains: Technologies— Communication —Intelligence

At the conceptual level the IoT technology represents the “middleware” between the implementation and grand challenges such as climate change, energy efficiency, mobility, digital society, global health and enabling technologies such as nanoelectronics, communication, sensors, smart phones, embedded systems, cloud computing and software technologies.

These challenges will eventually create new products, new services, new interfaces and new applications. The grand challenges will also drive the creation of new environments and intelligent ambients.


D-Business – 2016 onwards

D-business attributes:

Nearly all physical and virtual assets in the value chain are digital. Intelligent “things” are part of end-to-end processes. Intelligent agents take care of business by making decisions based on context.

Consumer and business solution modules are engaged via digital means. Most sales, deliveries and services are automated. Most analog or human dependent tasks are eliminated by automation using IoT, intelligent agents and robots.

Employees are engaged via digital means and collaborate in teams.

Tangible revenue and value are generated in a digital manner.

Things (physical and virtual) become agents of themselves for people and business and are able to provide services and answers to requests in the place of humans

DIGITAL BUSINESS IS A NEW BUSINESS ENVIRONMENT IN WHICH THE PHYSICAL AND VIRTUAL WORLDS HAVE MERGED. – Fredy Valente -

IoT allied with the development of emergent Internet Technologies such as IoE, IoP, IoM, IoS and business solutions form the infrastructure to the digital society based on knowledge and innovation.


Technological Trends

Re-design of mechnisms to find, fetch and transmit data which is collected and enchanged by interconnect IoT objects: todas energy consumption is at its limits

Autonomic Energy Harvesting devices and systems: from tiniest smart dust to huge data centers

Miniturization of devices with the objective on reaching a single electron transistor (depends heavily on new discoveries in physics)

Autonomous and responsible behaviour of resources: systems / devices should become self-managed / self-healed and self-configured.

The Key to address these macro trends in IoT is research and development in global intersectoral / interdisciplinary areas. High degree of complexity.


Applications: Smart Environments


Applications – IoT

DC-UFSCAR INTRODUÇÃO A LÓGICA – 2016 / SEM-1 Prof. Fredy

Social media analysis / Data and Event Visualisation

27

City Infrastructure

Tweets from a city

P. Anantharam, P. Barnaghi, K. Thirunarayan, A. Sheth, "Extracting city events from social streams,“, ACM Transactions on TICS, 2014.


Some IoT Challenges – in conclusion

28

•IoT data analytics are a new challenge to big data analytics.

•Data collection in the IoT challenges the bandwidth, network, energyand other resources.

•Data collection, delivery and processing is also depended on multiple layers of the network – there are lots of work here !

•We need more resource-aware data analytics methods and cross-layer optimisations – some decisions need to be made locally !

•The solutions should work across different systems and multiple platforms (Ecosystem of systems).

•Data sources are more than physical (sensory) observation – virtual smart objects are also a part of IoT !

•The IoT requires integration and processing of physical-cyber-social data : huge challenge !

•The extracted insights and information should be converted to a feedback and/or actionable information – remote and monitoring intelligent control challenge !!


Future Developments (1)



Future Developments (2)



Research Needs (1)



Research Needs (2)



Research Needs (3)



Research Needs (4)



Q & A

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