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Internet of Things
and Web Technology
C.K.Pithawala College Of
Engineering and Technology
TOPICS
• The internet of things today
• Time for convergence
• Towards IoT universe
• Internet Of Things Vision
• IoT Strategic Research and Innovation direction
• IoT Application
• Future Internet Technologies
• Infrastructure
• Network and Communication
• Process
• Data Management
• Security, Privacy and Trust
• Device level energy issues
• IoT Related Standardization
• Recommendation on Research Topics
The internet of things today
• What is iot?
The Internet of Things (IoT) is the
network of physical objects—devices,
vehicles, buildings and other items
embedded with electronics, software,
sensors, and network connectivity—that
enables these objects to collect and
exchange data.
What can be done with IoT?
 The possibilities are endless, but as devices start to
communicate with each other through the web,
several applications can be implemented:
 Smart Parking
 Smart Buildings / Offices / Houses
 Pollution Detection
 Detection of Explosive and Hazardous Gases in the
Industry
 Traffic Congestion Monitoring
 Smart & Adaptive Logistics Based on Real Time Data
 Vital Signs Detection and Medical Monitoring
CHARACTERISTICS
The fundamental characteristics of the IoT are
as follows:
1. Interconnectivity
2. Heterogeneity
3. Things related services
4. Dynamic changes
5. Enormous scale
6. Connectivity
7. Safety
Components of IoT
Internet
of
Things
Control
units
Sensor
Communi
cation
modules
Power
sources
Technology
& protocols
Advantages of IoT:
1. Improved customer communication
2. Support for technology optimization
3. Support wide range of data
collection
4. Reduced waste
5. Save time
Disadvantages of IoT:
1. Loss of privacy & security
2. Flexibility
3. Complexity
4. Compatibility
Time for convergence
The following will likely provide the
foundation for a step forward
to the Internet of Things:
1. Coherence of object capabilities and
behaviour
2. Coherence of application interactivity
3. Coherence of corresponding technology
approaches
4. Coherence of real and virtual worlds
Towards IoT universe
The forthcoming Internet of Things related research in the scope of Horizon
2020 and corresponding national research programs will address the matters,
challenges from a societal and policy perspective remain equally important, in
particular the following:
1. Fostering of a consistent, interoperable and accessible Internet of Things
across sectors, including standardisation.
2. Directing effort and attention to important societal application areas such as
health and environment, including focus on low energy consumption.
3. Offering orientation on security, privacy, trust and ethical aspects in the
scope of current legislation and development of robust and future-proof
general data protection rules.
4. Providing resources like spectrum allowing pan-European service provision
and removal of barriers such as roaming.
5. Maintaining the Internet of Things as an important subject for international
cooperation both for sharing best practises and developing coherent
strategies.
Internet Of Things Vision
Era of internet of things
Internet Of Things Vision
• The Internet-of-Things is emerging as one of the
major trends shaping the development of
technologies.
• The shift from an Internet used for
interconnecting end-user devices to an Internet
used for interconnecting physical objects that
communicate with each other and/or with humans
in order to offer a given service.
• From a conceptual standpoint, the IoT builds on
three pillars, related to the ability of smart objects
to:
(i) be identifiable (anything identifies itself),
(ii) to communicate (anything communicates)
(iii) to interact (anything interacts)
1) Devices heterogeneity.
2) Scalability.
3) Emergency optimized solution.
4) Self organizing capabilities.
5) Data management.
Internet Of Things Vision
Research Challenges: cities
• Smart Parking: Monitoring of parking spaces availability in
the city.
• Structural health: Monitoring of vibrations and material
conditions in buildings, bridges and historical monuments.
• Noise Urban Maps: Sound monitoring in bar areas and
centric zones in real time.
• Traffic Congestion: Monitoring of vehicles and pedestrian
levels to optimize driving and walking routes.
• Smart Lightning: Intelligent and weather adaptive lighting
in street lights.
• Waste Management: Detection of rubbish levels in
containers to optimize the trash collection routes.
• Intelligent Transportation Systems: Smart Roads and
Intelligent Highways with warning messages and
diversions according to climate conditions and unexpected
events like accidents or traffic jams.
Research Challenges: cities
Residential Building System
Research Challenges:
Environment
• Forest Fire Detection: Monitoring of
combustion gases and preemptive fire
conditions to define alert zones.
• Air Pollution: Control of CO 2 emissions of
factories, pollution emitted by cars and toxic
gases generated in farms.
• Landslide and Avalanche Prevention:
Monitoring of soil moisture, vibrations and
earth density to detect dangerous patterns in
land conditions.
• Earthquake Early Detection: Distributed
control in specific places of tremors.
Research Challenges: Water
• Water Quality: Study of water suitability in
rivers and the sea for fauna and eligibility
for drinkable use.
• Water Leakages: Detection of liquid
presence outside tanks and pressure
variations along pipes.
• River Floods: Monitoring of water level
variations in rivers, dams and reservoirs.
Research Challenges: Energy Smart
Grid, Smart Metering
• Smart Grid: Energy consumption monitoring
and management.
• Tank level: Monitoring of water, oil and gas
levels in storage tanks and cisterns.
• Photovoltaic Installations: Monitoring and
optimization of performance in solar energy
plants.
• Water Flow: Measurement of water pressure
in water transportation systems.
• Silos Stock Calculation: Measurement of
emptiness level and weight of the goods.
Applications of IOT
• Smart devices or “Connected devices ” as commonly called as, are
designed in such a way that they capture and utilize every bit of data
which you share or use in everyday life. And these devices will use
this data to interact with you on daily basis and complete tasks.
• This new wave of connectivity is going beyond laptops and
smartphones, it’s going towards connected cars, smart homes,
connected wearables, smart cities and connected healthcare.
Basically a connected life. According to Gartner report, by 2020
connected devices across all technologies will reach to 20.6 billion.
Applications of IOT
Smart home
• It involves the control and automation of lighting, heating (such
as smart thermostats), ventilation, air conditioning (HVAC), and
security, as well as home appliances such as washer/dryers, ovens
or refrigerators/freezers.
• Wi-Fi is often used for remote monitoring and control. Home
devices, when remotely monitored and controlled via the
Internet, are an important constituent of the Internet of Things.
• Modern systems generally consist of switches and sensors
connected to a central hub sometimes called a "gateway" from
which the system is controlled with a user interface that is
interacted either with a wall-mounted terminal, mobile phone
software, tablet computer or a web interface, often but not
always via Internet cloud services.
Applications of IOT
Smart home
• While there are many competing vendors, there are very few world-wide
accepted industry standards and the smart home space is heavily
fragmented. Popular communications protocol for products
include X10, Ethernet, RS-485, 6LoWPAN, Bluetooth LE (BLE), ZigBee and Z-
Wave, or other proprietary protocols all of which are incompatible with each
other. Manufacturers often prevent independent implementations by
withholding documentation and by litigation.
• The home automation market was worth US$5.77 billion in 2015, predicted
to have a market value over US$10 billion by the year 2020.
Internet enabled cat feeder
CITIB-AMX control panelRoom control unit
Applications of IOT
Wearables
• You'll find wearable technology for every level of fitness, whether
you want to monitor everyday activity, start a fitness program or
train for an athletic competition. And when you pair your
wearable tech device with a compatible app, it's easy to set
fitness goals and log your progress. Many activity trackers are
worn on your wrist, and you'll find a variety of styles that look like
bracelets or watches.
Smartwatch Options
A popular wearable technology option is the smartwatch. These stylish
yet functional devices allow you to conveniently and discreetly manage
your digital life. Smartwatches sync with your iPhone or android phone
and can even double as activity trackers. Options like the Apple
watch deliver alerts, notifications and apps to your wrist. Browse a
variety styles and brands to find the best smartwatch option to fit your
lifestyle.
Applications of IOT
Wearables
Usage
Wearable technology usage can be categorized into two major categories;
• personal usage
• business usage4
Whether for personal or business use, wearable tech gadgets are primarily
used for any one of the following functions;
• As a fashion statement
• As a fitness tracker
• As a treatment for hearing impairments
• As a sport tracker
• To synchronize data and communication from other gadgets
• For specific health issue monitoring, for example stress management
• As navigation tools
• As media devices
• As communication gadgets
Applications of IOT
Smart City
• Smart city spans a wide variety of use cases, from traffic management
to water distribution, to waste management, urban security and
environmental monitoring. Its popularity is fueled by the fact that
many Smart City solutions promise to alleviate real pains of people
living in cities these days. IoT solutions in the area of Smart City solve
traffic congestion problems, reduce noise and pollution and help make
cities safer.
• A smart city utilizes IoT sensors, actuators and technology to connect
components across the city, and it impacts every layer of a city, from
underneath the streets, to the air that citizens are breathing. Data
from all segments is analyzed, and patterns are derived from the
collected data.
Applications of IOT
Smart City
• Several concepts of the Smart city rely heavily on the use of technology; a
technological Smart City is not just one concept but there are different
combinations of technological infrastructure that build a concept of smart
city.
• Digital city: it combines service oriented infrastructure, innovation services and
communication infrastructure
• Virtual city: In these kinds of cities functions are implemented in a cyberspace; it
includes the notion of hybrid city, which consists of a reality with real citizens and
entities and a parallel virtual city of real entities and people.
• Information city: It collects local information and delivered them to the public
portal; In that city, many inhabitants are able to live and even work on the Internet
because they could obtain every information through IT infrastructures, thanks to
the sharing information method among citizens themselves.
• Intelligent city: it involves function as research or technological innovation to
support learning and innovation procedure.
• Ubiquitous city (U-city): It creates an environment that connect citizens to any
services through any device.
Applications of IOT
Smart grids
• A smart grid is an electrical grid which includes a variety of
operational and energy measures including smart meters, smart
appliances, renewable energy resources, and energy efficient
resources. Electronic power conditioning and control of the
production and distribution of electricity are important aspects of
the smart grid.
Applications of IOT
Smart grids
Features of the smart grid:
 Reliability
 Flexibility in network topology
 Efficiency
 Load adjustment/Load
balancing
 Peak curtailment/leveling and
time of use pricing
 Sustainability
 Market-enabling
 Demand response support
 Platform for advanced services
 Provision megabits, control
power with kilobits, sell the rest
Technologies:
 Smart meters
 Phasor measurement units
 Smart power generation using
advanced components
 wind turbines
 solar cells
 Power system automation
Applications of IOT
Smart retail
• Automated retail is the category of self-service, standalone
kiosks in heavily trafficked locations such as airports, malls and
resorts, and convenience store's.
• Consumers select products using a touchscreen interface, pay
for purchases using a credit or debit card and then the product
is dispensed, sometimes via an internal robotic arm in the
machine.
• Smartphones will be the way for retailers to remain connected
with their consumers even out of store. Interacting through
Smartphones and using Beacon technology can help retailers
serve their consumers better. They can also track consumers
path through a store and improve store layout and place
premium products in high traffic areas.
Applications of IOT
Smart Agriculture
• Smart Farming should provide the farmer with added value in the
form of better decision making or more efficient exploitation
operations and management. In this sense, smart farming is
strongly related, to three interconnected technology fields
addressed by Smart Network:
o Management Information Systems: Planned systems for
collecting, processing, storing, and disseminating data in the form
needed to carry out a farm’s operations and functions.
o Precision Agriculture: Management of spatial and temporal
variability to improve economic returns following the use of
inputs and reduce environmental impact.
o Agricultural automation and robotics: The process of applying
robotics, automatic control and artificial intelligence techniques
at all levels of agricultural production, including farmbots and
farm drones.
Applications of IOT
Smart Agriculture
Applications of IOT
Smart Healthcare
• Smart systems are critical in driving innovations in the field of
medical technology, as they provide the basis for information-based
care and cure.
• The integration of micro sensors and micro-actuators in products will
provide the healthcare professional to better treat and take care of
patients in the hospital and at home.
• The seamless linking of microsystems to a telemetric and tele
diagnostic infrastructure will significantly reduce response time, and
simultaneously contribute to containing public healthcare costs
• Successful new products require joint technological development,
and clinical development & validation (and business model
innovation)
• Multidisciplinary collaboration across industries and with multiple
academic partners (including those with access to clinical
applications) is key
Applications of IOT
Smart Healthcare
Applications of IOT
Smart Vehicles
Target users
•Automotive
•Security & insurance
•Transport & infrastructure
companies
•Administration/
governments
Opportunity areas
•Autonomous vehicles
•Connected bus-stops
•Connected trucks
•Connected cars
Intelligent transportation systems (ITS) are advanced
applications which, without embodying intelligence as such, aim to
provide innovative services relating to different modes of transport
and traffic management and enable various users to be better
informed and make safer, more coordinated, and 'smarter' use of
transport networks. They are considered a part of the Internet of
things.
Future internet technology
infrastructure
1. Cloud computing
2. IoT semantic technologies
3. Autonomy
4. Infrastructure
What is Cloud computing ?
• Cloud Computing is used to describe a new
class of network based computing that takes
place over the Internet,
– basically a step on from Utility Computing
– a collection/group of integrated and
networked hardware, software and
Internet infrastructure (called a platform).
– Using the Internet for communication and
transport provides hardware, software and
networking services to clients.
• These platforms
– hide the complexity and details of the underlying
infrastructure from users
– applications by providing very simple graphical
interface or API
– provides on demand services, that are always on,
anywhere, anytime and any place.
– Pay for use and as needed,
– elastic scale up and down in capacity and
functionalities
• The hardware and software services are available to
general public, enterprises, corporations and
businesses markets.
What is Cloud computing ?
Characteristics of cloud data
• A number of characteristics define cloud data,
applications services and infrastructure:
– Remotely hosted: Services or data are hosted on
remote infrastructure.
– Ubiquitous: Services or data are available from
anywhere.
– Commoditised: The result is a utility computing
model similar to traditional that of traditional
utilities, like gas and electricity - you pay for what
you would want!
• Shared pool of configurable computing resources
• On-demand network access
• Provisioned by the Service Provider
Characteristics of Cloud
Computing
Common Characteristics:
Low Cost Software
Virtualization Service Orientation
Advanced Security
Homogeneity
Massive Scale Resilient Computing
Geographic Distribution
Essential Characteristics:
Resource Pooling
Broad Network Access Rapid Elasticity
Measured Service
On Demand Self-Service
Characteristics of Cloud
Computing
• The “no-need-to-know” in terms of the underlying details of
infrastructure, applications interface with the infrastructure via the
APIs.
• The “flexibility and elasticity” allows these systems to scale up and
down at will
– utilizing the resources of all kinds
• The “pay as much as used and needed” type of utility computing and
the “always on!, anywhere and any place” type of network-based
computing.
• Cloud are transparent to users and applications, they can be built in
multiple ways
– branded products, proprietary open source, hardware or software,
or just off-the-shelf PCs.
• In general, they are built on clusters of PC servers and off-the-shelf
components plus Open Source software combined with in-house
applications and/or system software.
Cloud Computing Service
Layers
Advantages
• Lower computer costs
• Improved performance
• Reduced software costs
• Instant software updates
• Improved document format compatibility
• Unlimited storage capacity
• Increased data reliability
• Universal document access
• Latest version availability
• Easier group collaboration
• Device independence
Disadvantages
• Requires a constant Internet connection
• Does not work well with low-speed connections
• Features might be limited:
– For example, you can do a lot more with Microsoft
PowerPoint than with Google Presentation's web-
based offering
• Stored data might not be secure
• Stored data can be lost
• Scheduling is important with this
type of application
Semantics
• Semantics and Data
– Data with semantic annotations
– Provenance, quality of information
– Interpretable formats
– Links and interconnections
– Background knowledge, domain
information
– Hypotheses, expert knowledge
– Adaptable and context-aware solutions
Semantic technologies in the IoT
• Applying semantic technologies to IoT can
support:
– Interoperability
– effective data access and integration
– resource discovery
– reasoning and processing of data
– knowledge extraction (for automated
decision making and management)
Semantic modeling
• Lightweight:
– experiences show that a lightweight ontology model
that well balances expressiveness
– inference complexity is more likely to be widely
adopted and reused
– large number of IoT resources and huge amount of
data need efficient processing
• Compatibility:
– an ontology needs to be consistent with those well
designed,
– existing ontologies to ensure compatibility wherever
possible.
• Modularity:
– modular approach to facilitate ontology evolution,
– extension and integration with external ontologies.
• However, we should design
and use the semantics
carefully and consider the
constraints and dynamicity
of the IoT environments.
#1: Design for large-scale and provide tools
and APIs.
#2: Think of who will use the semantics and
how when you design your models.
#3: Provide means to update and change the
semantic annotations.
#4: Create tools for validation and
interoperability testing.
#5: Create taxonomies and vocabularies.
#6: Of course you can always create a better
model, but try to re-use existing ones as much
as you can.
#7: Link your data and descriptions to other existing
resources.
#8: Define rules and/or best practices for providing
the values for each attribute.
#9: Remember the widely used semantic
descriptions on the Web are simple ones like
FOAF.
#10: Semantics are only one part of the solution
and often not the end-product so the focus of the
design should be on creating effective methods,
tools and APIs to handle and process the
semantics.
Query methods, machine learning, reasoning and
data analysis techniques and methods should be
able to effectively use these semantics.
Semantics: services and application services models
and business process description models
Semantics: domain knowledge domain ontologies
and knowledge base
Semantics: devices, resources, and data description
models
Semantics: real world objects thing and entity
descriptions models
Securityprivacyandtrust
Semantic related issues
• The current IoT data communications often rely on binary
or syntactic data models which lack of providing machine
interpretable meanings to the data.
– Syntactic representation or in some cases XML-based
data
– Often no general agreement on annotating the data
• requires a pre-agreement between different parties
to be able to process and interpret the data
– Limited reasoning based on the content and context
data
– Limited interoperability in data and resource/device
description level
– Data integration and fusion issues
• Overall, we need semantic technologies in the IoT and
these play a key role in providing interoperability.
Autonomy
• There is still a lack of research on how to adopt and tailor existing
research on autonomic computing to the specific characteristic of
CPS,such as high dynamicity and distribution ,real time nature
,resource constraints and loss environments and .most existing
research in self aware Iot is lacking experimentation for validation.
• Autonomy in Iot can be realized by implementing
self-managing system
• Self management is the property of a system to
achieve management and maintenance of its
resources intrinsically and internally.
• managment and maintenance is realized through
many levels of decision making.
• management scope extends to access management
device management thus for self management
decision making in Iot should pertain to this scope of
Iot
• An autonomic computing system is required to be self
managing with minimum human interface.
Autonomy
Characteristics of AC(Autonomy
computing) system:
Self configuring
Self healing
Self optimizing
Self protecting
Infrastructure
• A category of cloud services which provides capability to
provision processing, storage, intra-cloud network connectivity
services, and other fundamental computing resources of the
cloud infrastructure.
• Iot refers to the set of devices and system that that
interconnected
real world sensors and actuators to the internet.
• Includes many different types of system such as
– Mobile devices
– Smart meters and objects
– Wearable device including clothing
– Health care implants
– Smart watch and fitness devices
– Internet connected automobile
– Home automation system, including thermostats, lighting and
home security
Basic IoT infrastructure
• Required diverse sensor and actuators.
• IoT devices and services should be able to
connect seamlessly and on a plug and play
basis how your device connects to the rest of
the world is a key consideration for IoT
products.
• To work with all feature of IoT different types
of application must run on it devices used in
IoT must supporting plug and play facilities
• Support to finding the things required
• An app may run anywhere including things
themselves.
Basic IoT infrastructure
Networks and Communication
and Processes
• Present communication technologies
span the globe in wireless and wired
networks and support global
communication by globally-accepted
communication standards.
Networks and Communication:
• Internet of things is an integrated part of
future internet including existing and evolving
internet and network developments.
• IOT allows communication among very
heterogeneous devices connected via a very
wide range of networks through the internet
infrastructure.
Networks and Communication:
• IOT devices and resources are any kind of
device connected to internet, from existing
devices, such as servers, laptops, personal
computers, to emerging devices such as smart
phones, smart meters, sensors, identification
readers and appliances.
• Capturing real world data, information and
knowledge and events is becoming increasingly
easier with sensor networks, social media
sharing, location based services and emerging
IOT applications.
Networks and Communication:
• Embedding real world information into networks,
services and applications is one of the aim of IOT
technology by using enabling technologies like wireless
sensor and actuator networks, IOT devices and RFID.
• The internet of things infrastructure allows
combinations of smart objects, sensor network
technologies, and human beings using different
communication protocols and realizes a dynamic
heterogeneous network that can be deployed also in
remote spaces.
• Network users will be humans, machines, things and
group of them.
Networks and Communication:
• Capabilities such as self-awareness, context
awareness and inter machine communication are
considered a high property for the IOT.
• New smart antennas that can be embedded in the
objects and made of new materials are the
communication means that will enable new
advanced communication systems on chip.
• Network users will be humans, machines, things
and group of them.
Communication Technology:
• Communication to enable information exchange
between “smart things/objects” and gateways
between those “smart things/objects” and internet.
• Communication with sensor for capturing and
representing the physical world in the digital world.
• Communication with actuators to perform action in
the physical world triggered in the digital world.
Communication Technology:
• Communication with distributed storage units for data
collection from sensors, identification and tracking
systems.
• Communication for interaction with humans in the
physical world.
• Communication and processing to provide data mining
and services.
• Communication for physical world localization and
tracking.
Process:
• The deployment of IOT technologies will
significantly impact and change the way
enterprises do business as well as interactions
between different parts of the society, affecting
many processes.
• The main benefits of IOT integration is that
processes become more adaptive to what is
actually happening in the real world.
• Processes become more adaptive after an IOT
integration.
• Data collection is based on the event or entity.
• When data is collected from the sensor or real time
data , integration processes happens.
• Such events can occur at any time in the process.
• Event occurrence probability is very low.
• How to react to a single event can depend on the
context.
• Example: the set of events that have been detected
previously.
Adaptive and Event-driven
Processes:
• When dealing with events coming from the physical
world, a degree of unreliability and uncertainty is
introduced into the processes.
• If decisions in a business process are to be taken
based on events that have some uncertainty
attached, it makes sense to associate each of these
events with some value for the quality of information.
• Data as well as resources are inherently unreliable.
• This is because of failure of the hosting device.
• Processing relying on such resources need to be able
to adapt to such situations.
• It is necessary to detect a failure.
• The quality of the generated reports should be
regularly audited for correctness.
Processes Dealing with
Unreliable Data:
Data Management
• Data management is to manage the data those are
collected from physical world.
• Data management is a crucial aspect in the Internet
of Things.
• When considering a world of objects
interconnected and constantly exchanging all types
of information, the volume of the generated data
and the processes involved in the handling of those
data become critical.
• There are many technologies and factors involved
in the “data management” within the IOT context.
Data Management
• Some of the most relevant concepts which enable
us to understand the challenges and
opportunities of data management are:
 Data Collection and Analysis
 Big Data
 Semantic Sensor Networking
 Virtual Sensors
 Complex Event Processing.
Data Collection and
Analysis(DCA)
• Data Collection and Analysis modules or capabilities are
the essential components of any IOT platform or system.
• The DCA module is part of the core layer of any IOT
platform. Some of the main functions of a DCA module
are:
 User/customer data storing:
Provides storage of the customer’s
information collected by sensors
 User data & operation modelling:
Allows the customer to create new sensor
data models to accommodate collected
information and the modelling of the
supported operations
Data Collection and
Analysis(DCA)
 On demand data access:
Provides APIs to access the collected data
 Device event
publish/subscribe/forwarding/notification:
Provides APIs to access the collected data
in real time conditions
 Customer rules/filtering:
Allows the customer to establish its own
filters and rules to correlate events
Data Collection and
Analysis(DCA)
 Customer task automation:
Provides the customer with the ability to manage
his automatic processes. Example: scheduled
platform originated data collection, …
 Customer workflows:
Allows the customer to create his own work flow to
process the incoming events from a device
 Multitenant structure:
Provides the structure to support multiple
organizations and reseller schemes.
Big Data
• Big data is about the processing and analysis of large data
repositories, so disproportionately large that it is impossible to
treat them with the conventional tools of analytical
databases.
• Big data requires exceptional technologies to efficiently process
large quantities of data within a tolerable amount of time.
• Technologies being applied to big data include
massively parallel processing (MPP) databases,
data-mining grids, distributed file systems, distributed
databases, cloud computing platforms, the Internet, and
scalable storage systems.
• These technologies are linked with many aspects derived from the
analysis of natural phenomena such as climate and seismic data to
environments such as health, safety or, of course, the business
environment.
Big Data
• Among the imminent research targets in this field are:
 Privacy. Big data systems must avoid any
suggestion that users and citizens in general
perceive that their privacy is being invaded.
 Integration of both relational and NoSQL
systems.
 More efficient indexing, search and processing
algorithms, allowing the extraction of results in
reduced time and, ideally, near to “real time”
scenarios.
 Optimized storage of data. Given the amount of
information that the new IOT world may
generate, it is essential to avoid that the storage
requirements and costs increase exponentially.
Semantic Sensor Networks and
Semantic Annotation of Data
• There are currently on-going efforts to define
ontologies and to create frameworks to apply
semantic Web technologies to sensor networks.
• The Semantic Sensor Web (SSW) proposes
annotating sensor data with spatial, temporal, and
thematic semantic metadata.
• This approach uses the current OGC and SWE
specifications and attempts to extend them with
semantic web technologies to provide enhanced
descriptions to facilitate access to sensor data.
Semantic Sensor Networks and
Semantic Annotation of Data
• In general , associating sensor and sensor network data
with other concepts (on the Web) and reasoning makes
the data information widely available for different
applications, front-end services and data consumers.
• The semantic description allow machines to interpret
links and relations between the different attributes of a
sensor description and also other data existing on the
Web or provided by other applications and resources.
• Utilizing and reasoning this information enables the
integration of the data on a wider scale, known as
networked knowledge.
• This machine-interpretable information (i.e. semantics)
is a key enabler for the semantic sensor networks.
Virtual Sensors
• A virtual sensor can be considered as a product of
spatial , temporal and/or thematic transformation
of raw or other virtual sensor producing data with
necessary provenance information attached to this
transformation.
• The data acquired by a set of sensors can be
collected ,processed according to an application-
provided aggregation function, and then perceived
as the reading of a single virtual sensor.
• The flow of information between real devices and
virtual sensors or actuators is presented in Figure.
Virtual Sensors
Virtual Sensors
• We follow that statement with this definition:
 A virtual sensor behaves just like a real sensor,
emitting time series data from a specified
geographic region with newly defined thematic
concepts or observations which the real sensors
may not have.
 A virtual sensor may not have any real sensor’s
physical properties such as manufacturer or battery
power information, but does have other properties,
such as: who created it; what methods are used,
and what original sensors it is based on.
Virtual Sensors
• The development of virtual sensors could be
approached following two different degrees of
complexity:
 The combination of a limited number of
related sensors or measurements to derive
new virtual data (usually done at the sensor
node or gateway level).
 The complex process of deriving virtual
information from a huge space of sensed
data (generally at the application level).
Complex Event Processing
• Virtual Sensors can be used to implement “single
sensors” from complex and multiple(actual) sensors
or various data sources ,thus providing a seamless
integration and processing of complex events in a
sensor (or Data Collection and Analysis) platform or
system.
• Complex event processing (CEP) is an emerging
network technology that creates actionable
,situational knowledge from distributed message-
based systems ,databases and applications in real
time or near real time.
• CEP can provide an organization with the capability
to define ,manage and predict events , situations,
exceptional conditions, opportunities and threats in
complex, heterogeneous networks.
Complex Event Processing
• CEP is a technology for extracting higher level
knowledge from situational information
abstracted from processing sensory information
and for low-latency filtering, correlating,
aggregating, and computing on real-world event
data.
• Most CEP solutions and concepts can be
classified into two main categories:
Complex Event Processing
 Computation-oriented CEP:
Focused on executing on-line algorithms as a
response to event data entering the system. A
simple example is to continuously calculate an
average based on data from the inbound
events
 Detection-oriented CEP:
Focused on detecting combinations of events
called event patterns or situations. A simple
example of detecting a situation is to look for a
specific sequence of events.
Security , privacy & Trust
• Security:
• As the IOT becomes a key element of the Future
Internet and a critical national/international
infrastructure, the need to provide adequate
security for the IOT infrastructure becomes ever
more important.
• Large-scale applications and services based on
the IOT are increasingly vulnerable to disruption
from attack or information theft.
• Advances are required in several areas to make
the IOT secure from those with malicious intent.
Privacy
• As much of the information in an IoT system may
be personal data, there is a requirement to
support anonymity and restrictive handling of
personal information.
• There are a number of privacy implications
arising from the ubiquity and pervasiveness of
IoT devices where further research is required,
including:
Privacy
• Preserving location privacy, where location can
be inferred from things associated with people.
• Prevention of personal information inference,
that individuals would wish to keep private,
through the observation of IOT-related
exchanges.
• Keeping information as local as possible using
decentralized computing and key management.
• Use of soft identities, where the real identity of
the user can be used to generate various soft
identities for specific applications.
Trust
• The trust framework needs to be able to deal
with humans and machines as users, i.e. it needs
to convey trust to humans and needs to be
robust enough to be used by machines without
denial of service.
• The development of trust frameworks that
address this requirement will require advances in
areas such as:
Trust
• Lightweight Public Key Infrastructures (PKI) as a
basis for trust management.
• Light weight key management systems to enable
trust relationships to be established.
• Quality of Information is a requirement for many
IOT-based systems where metadata can be used
to provide an assessment of the reliability of IoT
data.
• Decentralized and self-configuring systems as
alternatives to PKI for establishing trust
Device Technical Challenges
• One of the essential challenges in IoT is how to
interconnect “things” in an interoperable way
while taking into account the energy constraints,
knowing that the communication is the most
energy consuming task on devices.
1. Low Power Communication
Several low power communication
technologies have been proposed from different
standardization bodies.
Device Technical Challenges
• The most common ones are:
• IEEE802.15.4 has developed a low-cost , low-power
consumption, low complexity, low to medium range
communication standard
• Bluetooth low is the ultra-low power version of the
Bluetooth technology that is up to 15 times more
efficient than Bluetooth.
• Ultra-Wide Bandwidth (UWB) Technology is an
emerging technology in the IoT domain that
transmits signals across a much larger frequency
range than conventional systems
• RFID/NFC proposes a variety of standards to offer
contact less solutions.
Device Technical Challenges
2. Energy Harvesting
Energy harvesting (EH) must be chosen according
to the local environment.
• For outside or luminous indoor environments,
solar energy harvesting is the most appropriate
solution.
• The energy harvesting wireless sensor solution is
able to generate a signal from an extremely
small amount of energy.
Device Technical Challenges
3. Future Trends and Recommendations
• In the future, the number and types of IoT
devices will increase, therefore inter-operability
between devices will be essential. More
computation and yet less power and lower cost
requirements will have to be met. Technology
integration will be an enabler along with the
development of even lower power technology
and improvement of battery efficiency.
IoT Standardization cycle
IoT Related Standardization
• Standards mean is general common method , norms
and regulation , based on which some work must be
done.
• Standards can be official and binding (de jure) De facto
standards can be formed by companies or group of
companies which have come to market therefore used
methods.
• Standards play an important role in applying new
technologies.
• Standards are published documents that establish
specification and procedures designed to maximize the
reliability of materials.
• Standards address a range of issues , including but not
limited to various protocols to help product
functionality
Ides!
Project
approval
process
Develop
draft
standard
s
Sponsor
ballot
IEEE-SA
standards
board
approval
process
Publish
standards
Revise standard
Withdraw standardarchive
Max 4 years
Max
10
year
Standardization process
The Internet of Things (IoT)
Security Considerations for Higher
Education
Recommendations
Accommodate IoT with existing
practices:
– Policies, Procedures, & Standards
– Awareness Training
– Risk Management
– Vulnerability Management
– Forensics
Recommendations
• Plan for IoT growth:
– Additional types of logging, log storage: Can you
find the needle in the haystack?
– Increased network traffic: will your firewall / IDS
/ IPS be compatible and keep up?
– Increased demand for IP addresses both IPv4
and IPv6
– Increased network complexity – should these
devices be isolated or segmented?
Recommendations
• Strengthen partnerships with researchers,
vendors, and procurement department
Threat vs. Opportunity
• If misunderstood and misconfigured, IoT poses
risk to our data, privacy, and safety
• If understood and secured, IoT will enhance
communications, lifestyle, and delivery of
services
Threat
Opportunity
Internet Of things

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Internet Of things

  • 1. Internet of Things and Web Technology C.K.Pithawala College Of Engineering and Technology
  • 2. TOPICS • The internet of things today • Time for convergence • Towards IoT universe • Internet Of Things Vision • IoT Strategic Research and Innovation direction • IoT Application • Future Internet Technologies • Infrastructure • Network and Communication • Process • Data Management • Security, Privacy and Trust • Device level energy issues • IoT Related Standardization • Recommendation on Research Topics
  • 3. The internet of things today • What is iot? The Internet of Things (IoT) is the network of physical objects—devices, vehicles, buildings and other items embedded with electronics, software, sensors, and network connectivity—that enables these objects to collect and exchange data.
  • 4.
  • 5. What can be done with IoT?  The possibilities are endless, but as devices start to communicate with each other through the web, several applications can be implemented:  Smart Parking  Smart Buildings / Offices / Houses  Pollution Detection  Detection of Explosive and Hazardous Gases in the Industry  Traffic Congestion Monitoring  Smart & Adaptive Logistics Based on Real Time Data  Vital Signs Detection and Medical Monitoring
  • 6. CHARACTERISTICS The fundamental characteristics of the IoT are as follows: 1. Interconnectivity 2. Heterogeneity 3. Things related services 4. Dynamic changes 5. Enormous scale 6. Connectivity 7. Safety
  • 8. Advantages of IoT: 1. Improved customer communication 2. Support for technology optimization 3. Support wide range of data collection 4. Reduced waste 5. Save time
  • 9. Disadvantages of IoT: 1. Loss of privacy & security 2. Flexibility 3. Complexity 4. Compatibility
  • 11. The following will likely provide the foundation for a step forward to the Internet of Things: 1. Coherence of object capabilities and behaviour 2. Coherence of application interactivity 3. Coherence of corresponding technology approaches 4. Coherence of real and virtual worlds
  • 12. Towards IoT universe The forthcoming Internet of Things related research in the scope of Horizon 2020 and corresponding national research programs will address the matters, challenges from a societal and policy perspective remain equally important, in particular the following: 1. Fostering of a consistent, interoperable and accessible Internet of Things across sectors, including standardisation. 2. Directing effort and attention to important societal application areas such as health and environment, including focus on low energy consumption. 3. Offering orientation on security, privacy, trust and ethical aspects in the scope of current legislation and development of robust and future-proof general data protection rules. 4. Providing resources like spectrum allowing pan-European service provision and removal of barriers such as roaming. 5. Maintaining the Internet of Things as an important subject for international cooperation both for sharing best practises and developing coherent strategies.
  • 13. Internet Of Things Vision Era of internet of things
  • 14. Internet Of Things Vision • The Internet-of-Things is emerging as one of the major trends shaping the development of technologies. • The shift from an Internet used for interconnecting end-user devices to an Internet used for interconnecting physical objects that communicate with each other and/or with humans in order to offer a given service. • From a conceptual standpoint, the IoT builds on three pillars, related to the ability of smart objects to: (i) be identifiable (anything identifies itself), (ii) to communicate (anything communicates) (iii) to interact (anything interacts)
  • 15. 1) Devices heterogeneity. 2) Scalability. 3) Emergency optimized solution. 4) Self organizing capabilities. 5) Data management. Internet Of Things Vision
  • 17. • Smart Parking: Monitoring of parking spaces availability in the city. • Structural health: Monitoring of vibrations and material conditions in buildings, bridges and historical monuments. • Noise Urban Maps: Sound monitoring in bar areas and centric zones in real time. • Traffic Congestion: Monitoring of vehicles and pedestrian levels to optimize driving and walking routes. • Smart Lightning: Intelligent and weather adaptive lighting in street lights. • Waste Management: Detection of rubbish levels in containers to optimize the trash collection routes. • Intelligent Transportation Systems: Smart Roads and Intelligent Highways with warning messages and diversions according to climate conditions and unexpected events like accidents or traffic jams. Research Challenges: cities
  • 19. Research Challenges: Environment • Forest Fire Detection: Monitoring of combustion gases and preemptive fire conditions to define alert zones. • Air Pollution: Control of CO 2 emissions of factories, pollution emitted by cars and toxic gases generated in farms. • Landslide and Avalanche Prevention: Monitoring of soil moisture, vibrations and earth density to detect dangerous patterns in land conditions. • Earthquake Early Detection: Distributed control in specific places of tremors.
  • 20. Research Challenges: Water • Water Quality: Study of water suitability in rivers and the sea for fauna and eligibility for drinkable use. • Water Leakages: Detection of liquid presence outside tanks and pressure variations along pipes. • River Floods: Monitoring of water level variations in rivers, dams and reservoirs.
  • 21. Research Challenges: Energy Smart Grid, Smart Metering • Smart Grid: Energy consumption monitoring and management. • Tank level: Monitoring of water, oil and gas levels in storage tanks and cisterns. • Photovoltaic Installations: Monitoring and optimization of performance in solar energy plants. • Water Flow: Measurement of water pressure in water transportation systems. • Silos Stock Calculation: Measurement of emptiness level and weight of the goods.
  • 22. Applications of IOT • Smart devices or “Connected devices ” as commonly called as, are designed in such a way that they capture and utilize every bit of data which you share or use in everyday life. And these devices will use this data to interact with you on daily basis and complete tasks. • This new wave of connectivity is going beyond laptops and smartphones, it’s going towards connected cars, smart homes, connected wearables, smart cities and connected healthcare. Basically a connected life. According to Gartner report, by 2020 connected devices across all technologies will reach to 20.6 billion.
  • 23. Applications of IOT Smart home • It involves the control and automation of lighting, heating (such as smart thermostats), ventilation, air conditioning (HVAC), and security, as well as home appliances such as washer/dryers, ovens or refrigerators/freezers. • Wi-Fi is often used for remote monitoring and control. Home devices, when remotely monitored and controlled via the Internet, are an important constituent of the Internet of Things. • Modern systems generally consist of switches and sensors connected to a central hub sometimes called a "gateway" from which the system is controlled with a user interface that is interacted either with a wall-mounted terminal, mobile phone software, tablet computer or a web interface, often but not always via Internet cloud services.
  • 24. Applications of IOT Smart home • While there are many competing vendors, there are very few world-wide accepted industry standards and the smart home space is heavily fragmented. Popular communications protocol for products include X10, Ethernet, RS-485, 6LoWPAN, Bluetooth LE (BLE), ZigBee and Z- Wave, or other proprietary protocols all of which are incompatible with each other. Manufacturers often prevent independent implementations by withholding documentation and by litigation. • The home automation market was worth US$5.77 billion in 2015, predicted to have a market value over US$10 billion by the year 2020. Internet enabled cat feeder CITIB-AMX control panelRoom control unit
  • 25. Applications of IOT Wearables • You'll find wearable technology for every level of fitness, whether you want to monitor everyday activity, start a fitness program or train for an athletic competition. And when you pair your wearable tech device with a compatible app, it's easy to set fitness goals and log your progress. Many activity trackers are worn on your wrist, and you'll find a variety of styles that look like bracelets or watches. Smartwatch Options A popular wearable technology option is the smartwatch. These stylish yet functional devices allow you to conveniently and discreetly manage your digital life. Smartwatches sync with your iPhone or android phone and can even double as activity trackers. Options like the Apple watch deliver alerts, notifications and apps to your wrist. Browse a variety styles and brands to find the best smartwatch option to fit your lifestyle.
  • 26. Applications of IOT Wearables Usage Wearable technology usage can be categorized into two major categories; • personal usage • business usage4 Whether for personal or business use, wearable tech gadgets are primarily used for any one of the following functions; • As a fashion statement • As a fitness tracker • As a treatment for hearing impairments • As a sport tracker • To synchronize data and communication from other gadgets • For specific health issue monitoring, for example stress management • As navigation tools • As media devices • As communication gadgets
  • 27. Applications of IOT Smart City • Smart city spans a wide variety of use cases, from traffic management to water distribution, to waste management, urban security and environmental monitoring. Its popularity is fueled by the fact that many Smart City solutions promise to alleviate real pains of people living in cities these days. IoT solutions in the area of Smart City solve traffic congestion problems, reduce noise and pollution and help make cities safer. • A smart city utilizes IoT sensors, actuators and technology to connect components across the city, and it impacts every layer of a city, from underneath the streets, to the air that citizens are breathing. Data from all segments is analyzed, and patterns are derived from the collected data.
  • 28. Applications of IOT Smart City • Several concepts of the Smart city rely heavily on the use of technology; a technological Smart City is not just one concept but there are different combinations of technological infrastructure that build a concept of smart city. • Digital city: it combines service oriented infrastructure, innovation services and communication infrastructure • Virtual city: In these kinds of cities functions are implemented in a cyberspace; it includes the notion of hybrid city, which consists of a reality with real citizens and entities and a parallel virtual city of real entities and people. • Information city: It collects local information and delivered them to the public portal; In that city, many inhabitants are able to live and even work on the Internet because they could obtain every information through IT infrastructures, thanks to the sharing information method among citizens themselves. • Intelligent city: it involves function as research or technological innovation to support learning and innovation procedure. • Ubiquitous city (U-city): It creates an environment that connect citizens to any services through any device.
  • 29.
  • 30. Applications of IOT Smart grids • A smart grid is an electrical grid which includes a variety of operational and energy measures including smart meters, smart appliances, renewable energy resources, and energy efficient resources. Electronic power conditioning and control of the production and distribution of electricity are important aspects of the smart grid.
  • 31. Applications of IOT Smart grids Features of the smart grid:  Reliability  Flexibility in network topology  Efficiency  Load adjustment/Load balancing  Peak curtailment/leveling and time of use pricing  Sustainability  Market-enabling  Demand response support  Platform for advanced services  Provision megabits, control power with kilobits, sell the rest Technologies:  Smart meters  Phasor measurement units  Smart power generation using advanced components  wind turbines  solar cells  Power system automation
  • 32. Applications of IOT Smart retail • Automated retail is the category of self-service, standalone kiosks in heavily trafficked locations such as airports, malls and resorts, and convenience store's. • Consumers select products using a touchscreen interface, pay for purchases using a credit or debit card and then the product is dispensed, sometimes via an internal robotic arm in the machine. • Smartphones will be the way for retailers to remain connected with their consumers even out of store. Interacting through Smartphones and using Beacon technology can help retailers serve their consumers better. They can also track consumers path through a store and improve store layout and place premium products in high traffic areas.
  • 33.
  • 34. Applications of IOT Smart Agriculture • Smart Farming should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management. In this sense, smart farming is strongly related, to three interconnected technology fields addressed by Smart Network: o Management Information Systems: Planned systems for collecting, processing, storing, and disseminating data in the form needed to carry out a farm’s operations and functions. o Precision Agriculture: Management of spatial and temporal variability to improve economic returns following the use of inputs and reduce environmental impact. o Agricultural automation and robotics: The process of applying robotics, automatic control and artificial intelligence techniques at all levels of agricultural production, including farmbots and farm drones.
  • 36. Applications of IOT Smart Healthcare • Smart systems are critical in driving innovations in the field of medical technology, as they provide the basis for information-based care and cure. • The integration of micro sensors and micro-actuators in products will provide the healthcare professional to better treat and take care of patients in the hospital and at home. • The seamless linking of microsystems to a telemetric and tele diagnostic infrastructure will significantly reduce response time, and simultaneously contribute to containing public healthcare costs • Successful new products require joint technological development, and clinical development & validation (and business model innovation) • Multidisciplinary collaboration across industries and with multiple academic partners (including those with access to clinical applications) is key
  • 38. Applications of IOT Smart Vehicles Target users •Automotive •Security & insurance •Transport & infrastructure companies •Administration/ governments Opportunity areas •Autonomous vehicles •Connected bus-stops •Connected trucks •Connected cars Intelligent transportation systems (ITS) are advanced applications which, without embodying intelligence as such, aim to provide innovative services relating to different modes of transport and traffic management and enable various users to be better informed and make safer, more coordinated, and 'smarter' use of transport networks. They are considered a part of the Internet of things.
  • 39.
  • 40. Future internet technology infrastructure 1. Cloud computing 2. IoT semantic technologies 3. Autonomy 4. Infrastructure
  • 41. What is Cloud computing ? • Cloud Computing is used to describe a new class of network based computing that takes place over the Internet, – basically a step on from Utility Computing – a collection/group of integrated and networked hardware, software and Internet infrastructure (called a platform). – Using the Internet for communication and transport provides hardware, software and networking services to clients.
  • 42. • These platforms – hide the complexity and details of the underlying infrastructure from users – applications by providing very simple graphical interface or API – provides on demand services, that are always on, anywhere, anytime and any place. – Pay for use and as needed, – elastic scale up and down in capacity and functionalities • The hardware and software services are available to general public, enterprises, corporations and businesses markets. What is Cloud computing ?
  • 43. Characteristics of cloud data • A number of characteristics define cloud data, applications services and infrastructure: – Remotely hosted: Services or data are hosted on remote infrastructure. – Ubiquitous: Services or data are available from anywhere. – Commoditised: The result is a utility computing model similar to traditional that of traditional utilities, like gas and electricity - you pay for what you would want!
  • 44.
  • 45. • Shared pool of configurable computing resources • On-demand network access • Provisioned by the Service Provider
  • 46. Characteristics of Cloud Computing Common Characteristics: Low Cost Software Virtualization Service Orientation Advanced Security Homogeneity Massive Scale Resilient Computing Geographic Distribution Essential Characteristics: Resource Pooling Broad Network Access Rapid Elasticity Measured Service On Demand Self-Service
  • 47. Characteristics of Cloud Computing • The “no-need-to-know” in terms of the underlying details of infrastructure, applications interface with the infrastructure via the APIs. • The “flexibility and elasticity” allows these systems to scale up and down at will – utilizing the resources of all kinds • The “pay as much as used and needed” type of utility computing and the “always on!, anywhere and any place” type of network-based computing. • Cloud are transparent to users and applications, they can be built in multiple ways – branded products, proprietary open source, hardware or software, or just off-the-shelf PCs. • In general, they are built on clusters of PC servers and off-the-shelf components plus Open Source software combined with in-house applications and/or system software.
  • 49. Advantages • Lower computer costs • Improved performance • Reduced software costs • Instant software updates • Improved document format compatibility • Unlimited storage capacity • Increased data reliability • Universal document access • Latest version availability • Easier group collaboration • Device independence
  • 50. Disadvantages • Requires a constant Internet connection • Does not work well with low-speed connections • Features might be limited: – For example, you can do a lot more with Microsoft PowerPoint than with Google Presentation's web- based offering • Stored data might not be secure • Stored data can be lost • Scheduling is important with this type of application
  • 51. Semantics • Semantics and Data – Data with semantic annotations – Provenance, quality of information – Interpretable formats – Links and interconnections – Background knowledge, domain information – Hypotheses, expert knowledge – Adaptable and context-aware solutions
  • 52. Semantic technologies in the IoT • Applying semantic technologies to IoT can support: – Interoperability – effective data access and integration – resource discovery – reasoning and processing of data – knowledge extraction (for automated decision making and management)
  • 53. Semantic modeling • Lightweight: – experiences show that a lightweight ontology model that well balances expressiveness – inference complexity is more likely to be widely adopted and reused – large number of IoT resources and huge amount of data need efficient processing • Compatibility: – an ontology needs to be consistent with those well designed, – existing ontologies to ensure compatibility wherever possible. • Modularity: – modular approach to facilitate ontology evolution, – extension and integration with external ontologies.
  • 54. • However, we should design and use the semantics carefully and consider the constraints and dynamicity of the IoT environments.
  • 55. #1: Design for large-scale and provide tools and APIs. #2: Think of who will use the semantics and how when you design your models. #3: Provide means to update and change the semantic annotations. #4: Create tools for validation and interoperability testing. #5: Create taxonomies and vocabularies. #6: Of course you can always create a better model, but try to re-use existing ones as much as you can.
  • 56. #7: Link your data and descriptions to other existing resources. #8: Define rules and/or best practices for providing the values for each attribute. #9: Remember the widely used semantic descriptions on the Web are simple ones like FOAF. #10: Semantics are only one part of the solution and often not the end-product so the focus of the design should be on creating effective methods, tools and APIs to handle and process the semantics. Query methods, machine learning, reasoning and data analysis techniques and methods should be able to effectively use these semantics.
  • 57. Semantics: services and application services models and business process description models Semantics: domain knowledge domain ontologies and knowledge base Semantics: devices, resources, and data description models Semantics: real world objects thing and entity descriptions models Securityprivacyandtrust
  • 58. Semantic related issues • The current IoT data communications often rely on binary or syntactic data models which lack of providing machine interpretable meanings to the data. – Syntactic representation or in some cases XML-based data – Often no general agreement on annotating the data • requires a pre-agreement between different parties to be able to process and interpret the data – Limited reasoning based on the content and context data – Limited interoperability in data and resource/device description level – Data integration and fusion issues • Overall, we need semantic technologies in the IoT and these play a key role in providing interoperability.
  • 59. Autonomy • There is still a lack of research on how to adopt and tailor existing research on autonomic computing to the specific characteristic of CPS,such as high dynamicity and distribution ,real time nature ,resource constraints and loss environments and .most existing research in self aware Iot is lacking experimentation for validation.
  • 60. • Autonomy in Iot can be realized by implementing self-managing system • Self management is the property of a system to achieve management and maintenance of its resources intrinsically and internally. • managment and maintenance is realized through many levels of decision making. • management scope extends to access management device management thus for self management decision making in Iot should pertain to this scope of Iot • An autonomic computing system is required to be self managing with minimum human interface. Autonomy
  • 61. Characteristics of AC(Autonomy computing) system: Self configuring Self healing Self optimizing Self protecting
  • 62. Infrastructure • A category of cloud services which provides capability to provision processing, storage, intra-cloud network connectivity services, and other fundamental computing resources of the cloud infrastructure. • Iot refers to the set of devices and system that that interconnected real world sensors and actuators to the internet. • Includes many different types of system such as – Mobile devices – Smart meters and objects – Wearable device including clothing – Health care implants – Smart watch and fitness devices – Internet connected automobile – Home automation system, including thermostats, lighting and home security
  • 64. • Required diverse sensor and actuators. • IoT devices and services should be able to connect seamlessly and on a plug and play basis how your device connects to the rest of the world is a key consideration for IoT products. • To work with all feature of IoT different types of application must run on it devices used in IoT must supporting plug and play facilities • Support to finding the things required • An app may run anywhere including things themselves. Basic IoT infrastructure
  • 65. Networks and Communication and Processes • Present communication technologies span the globe in wireless and wired networks and support global communication by globally-accepted communication standards.
  • 66. Networks and Communication: • Internet of things is an integrated part of future internet including existing and evolving internet and network developments. • IOT allows communication among very heterogeneous devices connected via a very wide range of networks through the internet infrastructure.
  • 67. Networks and Communication: • IOT devices and resources are any kind of device connected to internet, from existing devices, such as servers, laptops, personal computers, to emerging devices such as smart phones, smart meters, sensors, identification readers and appliances. • Capturing real world data, information and knowledge and events is becoming increasingly easier with sensor networks, social media sharing, location based services and emerging IOT applications.
  • 68. Networks and Communication: • Embedding real world information into networks, services and applications is one of the aim of IOT technology by using enabling technologies like wireless sensor and actuator networks, IOT devices and RFID. • The internet of things infrastructure allows combinations of smart objects, sensor network technologies, and human beings using different communication protocols and realizes a dynamic heterogeneous network that can be deployed also in remote spaces. • Network users will be humans, machines, things and group of them.
  • 69. Networks and Communication: • Capabilities such as self-awareness, context awareness and inter machine communication are considered a high property for the IOT. • New smart antennas that can be embedded in the objects and made of new materials are the communication means that will enable new advanced communication systems on chip. • Network users will be humans, machines, things and group of them.
  • 70. Communication Technology: • Communication to enable information exchange between “smart things/objects” and gateways between those “smart things/objects” and internet. • Communication with sensor for capturing and representing the physical world in the digital world. • Communication with actuators to perform action in the physical world triggered in the digital world.
  • 71. Communication Technology: • Communication with distributed storage units for data collection from sensors, identification and tracking systems. • Communication for interaction with humans in the physical world. • Communication and processing to provide data mining and services. • Communication for physical world localization and tracking.
  • 72. Process: • The deployment of IOT technologies will significantly impact and change the way enterprises do business as well as interactions between different parts of the society, affecting many processes. • The main benefits of IOT integration is that processes become more adaptive to what is actually happening in the real world.
  • 73. • Processes become more adaptive after an IOT integration. • Data collection is based on the event or entity. • When data is collected from the sensor or real time data , integration processes happens. • Such events can occur at any time in the process. • Event occurrence probability is very low. • How to react to a single event can depend on the context. • Example: the set of events that have been detected previously. Adaptive and Event-driven Processes:
  • 74. • When dealing with events coming from the physical world, a degree of unreliability and uncertainty is introduced into the processes. • If decisions in a business process are to be taken based on events that have some uncertainty attached, it makes sense to associate each of these events with some value for the quality of information. • Data as well as resources are inherently unreliable. • This is because of failure of the hosting device. • Processing relying on such resources need to be able to adapt to such situations. • It is necessary to detect a failure. • The quality of the generated reports should be regularly audited for correctness. Processes Dealing with Unreliable Data:
  • 75. Data Management • Data management is to manage the data those are collected from physical world. • Data management is a crucial aspect in the Internet of Things. • When considering a world of objects interconnected and constantly exchanging all types of information, the volume of the generated data and the processes involved in the handling of those data become critical. • There are many technologies and factors involved in the “data management” within the IOT context.
  • 76. Data Management • Some of the most relevant concepts which enable us to understand the challenges and opportunities of data management are:  Data Collection and Analysis  Big Data  Semantic Sensor Networking  Virtual Sensors  Complex Event Processing.
  • 77. Data Collection and Analysis(DCA) • Data Collection and Analysis modules or capabilities are the essential components of any IOT platform or system. • The DCA module is part of the core layer of any IOT platform. Some of the main functions of a DCA module are:  User/customer data storing: Provides storage of the customer’s information collected by sensors  User data & operation modelling: Allows the customer to create new sensor data models to accommodate collected information and the modelling of the supported operations
  • 78. Data Collection and Analysis(DCA)  On demand data access: Provides APIs to access the collected data  Device event publish/subscribe/forwarding/notification: Provides APIs to access the collected data in real time conditions  Customer rules/filtering: Allows the customer to establish its own filters and rules to correlate events
  • 79. Data Collection and Analysis(DCA)  Customer task automation: Provides the customer with the ability to manage his automatic processes. Example: scheduled platform originated data collection, …  Customer workflows: Allows the customer to create his own work flow to process the incoming events from a device  Multitenant structure: Provides the structure to support multiple organizations and reseller schemes.
  • 80. Big Data • Big data is about the processing and analysis of large data repositories, so disproportionately large that it is impossible to treat them with the conventional tools of analytical databases. • Big data requires exceptional technologies to efficiently process large quantities of data within a tolerable amount of time. • Technologies being applied to big data include massively parallel processing (MPP) databases, data-mining grids, distributed file systems, distributed databases, cloud computing platforms, the Internet, and scalable storage systems. • These technologies are linked with many aspects derived from the analysis of natural phenomena such as climate and seismic data to environments such as health, safety or, of course, the business environment.
  • 81. Big Data • Among the imminent research targets in this field are:  Privacy. Big data systems must avoid any suggestion that users and citizens in general perceive that their privacy is being invaded.  Integration of both relational and NoSQL systems.  More efficient indexing, search and processing algorithms, allowing the extraction of results in reduced time and, ideally, near to “real time” scenarios.  Optimized storage of data. Given the amount of information that the new IOT world may generate, it is essential to avoid that the storage requirements and costs increase exponentially.
  • 82. Semantic Sensor Networks and Semantic Annotation of Data • There are currently on-going efforts to define ontologies and to create frameworks to apply semantic Web technologies to sensor networks. • The Semantic Sensor Web (SSW) proposes annotating sensor data with spatial, temporal, and thematic semantic metadata. • This approach uses the current OGC and SWE specifications and attempts to extend them with semantic web technologies to provide enhanced descriptions to facilitate access to sensor data.
  • 83. Semantic Sensor Networks and Semantic Annotation of Data • In general , associating sensor and sensor network data with other concepts (on the Web) and reasoning makes the data information widely available for different applications, front-end services and data consumers. • The semantic description allow machines to interpret links and relations between the different attributes of a sensor description and also other data existing on the Web or provided by other applications and resources. • Utilizing and reasoning this information enables the integration of the data on a wider scale, known as networked knowledge. • This machine-interpretable information (i.e. semantics) is a key enabler for the semantic sensor networks.
  • 84. Virtual Sensors • A virtual sensor can be considered as a product of spatial , temporal and/or thematic transformation of raw or other virtual sensor producing data with necessary provenance information attached to this transformation. • The data acquired by a set of sensors can be collected ,processed according to an application- provided aggregation function, and then perceived as the reading of a single virtual sensor. • The flow of information between real devices and virtual sensors or actuators is presented in Figure.
  • 86. Virtual Sensors • We follow that statement with this definition:  A virtual sensor behaves just like a real sensor, emitting time series data from a specified geographic region with newly defined thematic concepts or observations which the real sensors may not have.  A virtual sensor may not have any real sensor’s physical properties such as manufacturer or battery power information, but does have other properties, such as: who created it; what methods are used, and what original sensors it is based on.
  • 87. Virtual Sensors • The development of virtual sensors could be approached following two different degrees of complexity:  The combination of a limited number of related sensors or measurements to derive new virtual data (usually done at the sensor node or gateway level).  The complex process of deriving virtual information from a huge space of sensed data (generally at the application level).
  • 88. Complex Event Processing • Virtual Sensors can be used to implement “single sensors” from complex and multiple(actual) sensors or various data sources ,thus providing a seamless integration and processing of complex events in a sensor (or Data Collection and Analysis) platform or system. • Complex event processing (CEP) is an emerging network technology that creates actionable ,situational knowledge from distributed message- based systems ,databases and applications in real time or near real time. • CEP can provide an organization with the capability to define ,manage and predict events , situations, exceptional conditions, opportunities and threats in complex, heterogeneous networks.
  • 89. Complex Event Processing • CEP is a technology for extracting higher level knowledge from situational information abstracted from processing sensory information and for low-latency filtering, correlating, aggregating, and computing on real-world event data. • Most CEP solutions and concepts can be classified into two main categories:
  • 90. Complex Event Processing  Computation-oriented CEP: Focused on executing on-line algorithms as a response to event data entering the system. A simple example is to continuously calculate an average based on data from the inbound events  Detection-oriented CEP: Focused on detecting combinations of events called event patterns or situations. A simple example of detecting a situation is to look for a specific sequence of events.
  • 91. Security , privacy & Trust • Security: • As the IOT becomes a key element of the Future Internet and a critical national/international infrastructure, the need to provide adequate security for the IOT infrastructure becomes ever more important. • Large-scale applications and services based on the IOT are increasingly vulnerable to disruption from attack or information theft. • Advances are required in several areas to make the IOT secure from those with malicious intent.
  • 92. Privacy • As much of the information in an IoT system may be personal data, there is a requirement to support anonymity and restrictive handling of personal information. • There are a number of privacy implications arising from the ubiquity and pervasiveness of IoT devices where further research is required, including:
  • 93. Privacy • Preserving location privacy, where location can be inferred from things associated with people. • Prevention of personal information inference, that individuals would wish to keep private, through the observation of IOT-related exchanges. • Keeping information as local as possible using decentralized computing and key management. • Use of soft identities, where the real identity of the user can be used to generate various soft identities for specific applications.
  • 94. Trust • The trust framework needs to be able to deal with humans and machines as users, i.e. it needs to convey trust to humans and needs to be robust enough to be used by machines without denial of service. • The development of trust frameworks that address this requirement will require advances in areas such as:
  • 95. Trust • Lightweight Public Key Infrastructures (PKI) as a basis for trust management. • Light weight key management systems to enable trust relationships to be established. • Quality of Information is a requirement for many IOT-based systems where metadata can be used to provide an assessment of the reliability of IoT data. • Decentralized and self-configuring systems as alternatives to PKI for establishing trust
  • 96. Device Technical Challenges • One of the essential challenges in IoT is how to interconnect “things” in an interoperable way while taking into account the energy constraints, knowing that the communication is the most energy consuming task on devices. 1. Low Power Communication Several low power communication technologies have been proposed from different standardization bodies.
  • 97. Device Technical Challenges • The most common ones are: • IEEE802.15.4 has developed a low-cost , low-power consumption, low complexity, low to medium range communication standard • Bluetooth low is the ultra-low power version of the Bluetooth technology that is up to 15 times more efficient than Bluetooth. • Ultra-Wide Bandwidth (UWB) Technology is an emerging technology in the IoT domain that transmits signals across a much larger frequency range than conventional systems • RFID/NFC proposes a variety of standards to offer contact less solutions.
  • 98. Device Technical Challenges 2. Energy Harvesting Energy harvesting (EH) must be chosen according to the local environment. • For outside or luminous indoor environments, solar energy harvesting is the most appropriate solution. • The energy harvesting wireless sensor solution is able to generate a signal from an extremely small amount of energy.
  • 99. Device Technical Challenges 3. Future Trends and Recommendations • In the future, the number and types of IoT devices will increase, therefore inter-operability between devices will be essential. More computation and yet less power and lower cost requirements will have to be met. Technology integration will be an enabler along with the development of even lower power technology and improvement of battery efficiency.
  • 101. IoT Related Standardization • Standards mean is general common method , norms and regulation , based on which some work must be done. • Standards can be official and binding (de jure) De facto standards can be formed by companies or group of companies which have come to market therefore used methods. • Standards play an important role in applying new technologies. • Standards are published documents that establish specification and procedures designed to maximize the reliability of materials. • Standards address a range of issues , including but not limited to various protocols to help product functionality
  • 103. The Internet of Things (IoT) Security Considerations for Higher Education
  • 104. Recommendations Accommodate IoT with existing practices: – Policies, Procedures, & Standards – Awareness Training – Risk Management – Vulnerability Management – Forensics
  • 105. Recommendations • Plan for IoT growth: – Additional types of logging, log storage: Can you find the needle in the haystack? – Increased network traffic: will your firewall / IDS / IPS be compatible and keep up? – Increased demand for IP addresses both IPv4 and IPv6 – Increased network complexity – should these devices be isolated or segmented?
  • 106. Recommendations • Strengthen partnerships with researchers, vendors, and procurement department
  • 107. Threat vs. Opportunity • If misunderstood and misconfigured, IoT poses risk to our data, privacy, and safety • If understood and secured, IoT will enhance communications, lifestyle, and delivery of services Threat Opportunity