Unit-8 Current Developments · Use of TV and toll-free telephones in business are not usually...

Unit-8

Current Developments

Compiled By:

Dr. Vanita Joshi

Unit-8 Currrent Development

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Content

• E-business

• Cloud Computing

• Big data

• Wireless Sensor Network

• Data Warehousing

• Data Mining

• Green Computing


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Unit-8 Currrent Development 3

What is E-Commerce?

• Electronic commerce or e-commerce refers to a wide range of

online business activities for products and services. It also pertains

to “any form of business transaction in which the parties interact

electronically rather than by physical exchanges or direct physical

contact.”

• Business activities running over the Internet and World Wide Web

platform

• Use of TV and toll-free telephones in business are not usually

associated with e-commerce


What is E-Commerce? (Continue…….)

• A more complete definition is: E-commerce is the use of

electronic communications and digital information processing

technology in business transactions to create, transform, and

redefine relationships for value creation between or among

organizations, and between organizations and individuals.

• Depending on the situation, electronic data interchange (EDI)

may or may not be associated with e-commerce. EDI is used for

business-to-business transactions


Pure Vs. Partial Electronic Commerce

–Three dimensions

• the product (service) sold [physical / digital]; • the process [physical / digital] • the delivery agent (or intermediary) [physical / digital]

–Traditional commerce

• all dimensions are physical

–Pure EC

• all dimensions are digital

–Partial EC

• all other possibilities include a mix of digital and physical dimensions


Is e-commerce the same as e-business?

e-commerce and e-business are generally used interchangeably, but they

are the distinct concepts.

In e-commerce, information and communications technology (ICT) is

used in inter-business or inter-organizational transactions (transactions

between and among firms/organizations) and in business-to-consumer

transactions (transactions between firms/organizations and individuals).

While in e-business, on the other hand, ICT is used to enhance one’s

business. It includes any process that a business organization (either a for-

profit, governmental or non-profit entity) conducts over a computer-

mediated network.


Three primary processes are enhanced in e-business:

1. Production processes, which include procurement, ordering and

replenishment of stocks; processing of payments; electronic links with

suppliers; and production control processes, among others.

2. Customer-focused processes, which include promotional and

marketing efforts, selling over the Internet, processing of customers’ purchase orders and payments, and customer support, among others.

3. Internal management processes, which include employee services,

training, internal information-sharing, video-conferencing, and

recruiting.

Electronic applications enhance information flow between production

and sales forces to improve sales force productivity. Workgroup

communications and electronic publishing of internal business

information are likewise made more efficient.


Types of E-Commerce

• Business-to-Business (B 2 B) e-commerce

• Business-to-Consumer ( B 2 C) e-commerce

• Consumer-to-consumer (C 2 C) e-commerce

• Business-to-Government (B 2 G) e-commerce

• Mobile Commerce (m-commerce)


Business-to-Business (B 2 B) e-commerce

• B2B e-commerce is simply defined as e-commerce between

companies.

• This is the type of e-commerce that deals with relationships between

and among businesses. About 80% of e-commerce is of this type.

• The B2B market has two primary components: e-frastructure and e-

markets.

• The more common B2B examples and best practice models are IBM,

Hewlett Packard (HP), Cisco and Dell. Cisco, for instance, receives

over 90% of its product orders over the Internet.


Business-to-Consumer ( B 2 C) e-commerce

• Business-to-consumer e-commerce, or commerce between

companies and consumers.

• B2C involves customers gathering information; purchasing

physical goods or information goods and receiving products

over an electronic network.

• It is the second largest and the earliest form of e-commerce.

Its origins can be traced to online retailing (or e-tailing). Thus,

the more common B2C business models are the online retailing

companies such as Amazon.com, Drugstore.com, Beyond.com.


Consumer-to-Consumer (C 2 C) e-commerce

• Consumer-to-consumer e-commerce or C2C is simply commerce

between private individuals or consumers.

• This type of e-commerce is characterized by the growth of

electronic marketplaces and online auctions, particularly in vertical

industries where firms/businesses can bid for what they want from

among multiple suppliers. It perhaps has the greatest potential for

developing new markets.


This type of e-commerce comes in at least three forms:

• Auctions facilitated at a portal, such as eBay, which allows

online real-time bidding on items being sold in the Web.

•Peer-to-peer systems, such as the Napster model (a protocol for

sharing files between users used by chat forums similar to IRC)

and other file exchange and later money exchange models.

• Classified ads at portal sites such as Excite Classifieds and

eWanted (an interactive, online marketplace where buyers and

sellers can negotiate and which features “Buyer Leads & Want

Ads”).


• Business-to-government e-commerce is generally defined as commerce between companies

and the public sector.

• It refers to the use of the Internet for public procurement, licensing procedures, and other

government-related operations.

• This kind of e-commerce has two features: first, the public sector assumes a pilot/leading role

in establishing e-commerce; and second, it is assumed that the public sector has the greatest

need for making its procurement system more effective.

• Web-based purchasing policies increase the transparency of the procurement process (and

reduces the risk of irregularities). To date, however, the size of the B2G e-commerce market as

a component of total e-commerce is insignificant, as government e-procurement systems

remain undeveloped.

Business-to-Government (B 2 G) e-commerce


Mobile Commerce (m-commerce)

• M-commerce (mobile commerce) is the buying and selling of

goods and services through wireless technology-i.e., handheld

devices such as cellular telephones and personal digital assistants

(PDAs).

• As content delivery over wireless devices becomes faster, more

secure, and scalable.

• Industries affected by m-commerce include:

* Financial services

* Telecommunications

* Service/retail

* Information services


Components of a typical successful E-Commerce

E-commerce does not refer merely to a firm putting up a Web site for

the purpose of selling goods to buyers over the Internet. But

number of technical as well as enabling issues have to be

considered.

A typical e-commerce transaction loop involves the following major

players and corresponding requisites:

• Seller

• Transaction Partners

• Consumers

• Business / Firm

• Government

• Internet

Big Data Unit-8 Currrent Development

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Introduction to Big Data

What is Big Data?

What makes data, “Big” Data?

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Big Data Definition

• No single standard definition…

“Big Data” is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and

analytics to manage it and extract value and hidden

knowledge from it…

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Characteristics of Big Data:

1-Scale (Volume)

• Data Volume

• 44x increase from 2009 2020

• From 0.8 zettabytes to 35zb

• Data volume is increasing exponentially

20 Exponential increase in

collected/generated data



2-Complexity (Varity) • Various formats, types, and structures

• Text, numerical, images, audio, video,

sequences, time series, social media

data, multi-dim arrays, etc…

• Static data vs. streaming data

• A single application can be

generating/collecting many types of

data

21 To extract knowledge all these types of

data need to linked together



3-Speed (Velocity) • Data is begin generated fast and need to be processed fast

• Online Data Analytics

• Late decisions missing opportunities

• Examples

• E-Promotions: Based on your current location, your purchase history, what

you like send promotions right now for store next to you

• Healthcare monitoring: sensors monitoring your activities and body

any abnormal measurements require immediate reaction

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Big Data: 3V’s

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Some Make it 4V’s

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Who’s Generating Big Data

Social media and networks

(all of us are generating data) Scientific instruments

(collecting all sorts of data)

Mobile devices

(tracking all objects all the time)

Sensor technology and networks

(measuring all kinds of data)

• The progress and innovation is no longer hindered by the ability to collect data

• But, by the ability to manage, analyze, summarize, visualize, and discover

knowledge from the collected data in a timely manner and in a scalable

fashion 25


The Model Has Changed…

• The Model of Generating/Consuming Data has Changed

Old Model: Few companies are generating data, all others are consuming data

New Model: all of us are generating data, and all of us are consuming data

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What’s driving Big Data

- Ad-hoc querying and reporting

- Data mining techniques

- Structured data, typical sources

- Small to mid-size datasets

- Optimizations and predictive analytics

- Complex statistical analysis

- All types of data, and many sources

- Very large datasets

- More of a real-time

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Big Data Technology

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Could Computing Unit-8 Currrent Development

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What is Cloud Computing? • Cloud Computing is a general term 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 and applications by

providing very simple graphical interface or API (Applications

Programming Interface).

30 Unit-8 Currrent Development

What is Cloud Computing?

• In addition, the platform 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


Cloud Summary • Cloud computing is an umbrella term used to refer to

Internet based development and services

• 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.

• Commodified: 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!


Cloud Architecture


What is Cloud Computing

34 Adopted from: Effectively and Securely Using the Cloud Computing Paradigm by peter Mell, Tim Grance

• Shared pool of configurable computing resources

• On-demand network access

• Provisioned by the Service Provider


Cloud Computing Characteristics

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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

Adopted from: Effectively and Securely Using the Cloud Computing Paradigm by peter Mell, Tim Grance Unit-8 Currrent Development

Cloud Service Models

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Software as a Service (SaaS)

Platform as a Service (PaaS)

Infrastructure as a Service (IaaS)

Google App

Engine

SalesForce CRM

LotusLive

Adopted from: Effectively and Securely Using the Cloud Computing Paradigm by peter Mell, Tim Grance Unit-8 Currrent Development

http://aws.amazon.com/

http://www.rackspace.com/index.php

SaaS Maturity Model

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Source: Frederick Chong and Gianpaolo Carraro, “Architectures Strategies for Catching the Long Tail”

Level 2: Configurable per

customer

Level 3: configurable &

Multi-Tenant-Efficient

Level 1: Ad-Hoc/Custom – One Instance per customer

Level 4: Scalable,

Configurable & Multi-Tenant-

Efficient


Different Cloud Computing Layers‏ Application Service

(SaaS)

Application Platform

Server Platform

Storage Platform Amazon S3, Dell, Apple, ...

3Tera, EC2, SliceHost,

GoGrid, RightScale, Linode

Google App Engine, Mosso,

Force.com, Engine Yard,

Facebook, Heroku, AWS

MS Live/ExchangeLabs, IBM,

Google Apps; Salesforce.com

Quicken Online, Zoho, Cisco


Services

Application

Development

Platform

Storage

Hosting

Cloud Computing Service Layers Description

Services – Complete business services such as PayPal,

OpenID, OAuth, Google Maps, Alexa

Services

Application

Focused

Infrastructure

Focused

Application – Cloud based software that eliminates the need

for local installation such as Google Apps, Microsoft Online

Storage – Data storage or cloud based NAS such as

CTERA, iDisk, CloudNAS

Development – Software development platforms used to

build custom cloud based applications (PAAS & SAAS) such

as SalesForce

Platform – Cloud based platforms, typically provided using

virtualization, such as Amazon ECC, Sun Grid

Hosting – Physical data centers such as those run by IBM,

HP, NaviSite, etc.


Basic Cloud

Characteristics

• 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

• utilising the resources of all kinds

• CPU, storage, server capacity, load balancing, and databases

• 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.


Basic Cloud

Characteristics

• 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.


Software as a Service

(SaaS) • SaaS is a model of software deployment where an

application is hosted as a service provided to

customers across the Internet.

• Saas alleviates the burden of software

maintenance/support

• but users relinquish control over software versions and

requirements.

• Terms that are used in this sphere include

• Platform as a Service (PaaS) and

• Infrastructure as a Service (IaaS)


Cloud Taxonomy


Cloud Storage

• Several large Web companies are now exploiting the

fact that they have data storage capacity that can be

hired out to others.

• allows data stored remotely to be temporarily cached on

desktop computers, mobile phones or other Internet-linked

devices.

• Amazon’s Elastic Compute Cloud (EC2) and Simple Storage Solution (S3) are well known examples

• Mechanical Turk


Amazon Simple Storage Service (S3)

• Unlimited Storage.

• Pay for what you use:

• $0.20 per GByte of data transferred,

• $0.15 per GByte-Month for storage used,

• Second Life Update:

• 1TBytes, 40,000 downloads in 24 hours - $200,


Advantages of Cloud Computing

• Lower computer costs: • You do not need a high-powered and high-priced computer to

run cloud computing's web-based applications.

• Since applications run in the cloud, not on the desktop PC, your desktop PC does not need the processing power or hard disk space demanded by traditional desktop software.

• When you are using web-based applications, your PC can be less expensive, with a smaller hard disk, less memory, more efficient processor...

• In fact, your PC in this scenario does not even need a CD or DVD drive, as no software programs have to be loaded and no document files need to be saved.



• Improved performance: • With few large programs hogging your computer's memory,

you will see better performance from your PC.

• Computers in a cloud computing system boot and run faster because they have fewer programs and processes loaded into memory…

• Reduced software costs: • Instead of purchasing expensive software applications, you

can get most of what you need for free-ish! • most cloud computing applications today, such as the Google Docs suite.

• better than paying for similar commercial software • which alone may be justification for switching to cloud applications.



• Instant software updates:

• Another advantage to cloud computing is that you are no longer faced

with choosing between obsolete software and high upgrade costs.

• When the application is web-based, updates happen automatically

• available the next time you log into the cloud.

• When you access a web-based application, you get the latest version

• without needing to pay for or download an upgrade.

• Improved document format compatibility.

• You do not have to worry about the documents you create on your

machine being compatible with other users' applications or OSes

• There are potentially no format incompatibilities when everyone is

sharing documents and applications in the cloud.


Advantages of Cloud Computing • Unlimited storage capacity: • Cloud computing offers virtually limitless storage.

• Your computer's current 1 Tbyte hard drive is small compared to the hundreds of Pbytes available in the cloud.

• Increased data reliability: • Unlike desktop computing, in which if a hard disk crashes

and destroy all your valuable data, a computer crashing in the cloud should not affect the storage of your data. • if your personal computer crashes, all your data is still out there in the

cloud, still accessible

• In a world where few individual desktop PC users back up their data on a regular basis, cloud computing is a data-safe computing platform!



• Universal document access: • That is not a problem with cloud computing, because you do

not take your documents with you.

• Instead, they stay in the cloud, and you can access them whenever you have a computer and an Internet connection

• Documents are instantly available from wherever you are

• Latest version availability: • When you edit a document at home, that edited version is

what you see when you access the document at work.

• The cloud always hosts the latest version of your documents • as long as you are connected, you are not in danger of having an outdated

version



• Easier group collaboration:

• Sharing documents leads directly to better collaboration.

• Many users do this as it is an important advantages of cloud

computing

• multiple users can collaborate easily on documents and projects

• Device independence.

• You are no longer tethered to a single computer or network.

• Changes to computers, applications and documents follow you

through the cloud.

• Move to a portable device, and your applications and

documents are still available.


Disadvantages of Cloud Computing

• Requires a constant Internet connection:

• Cloud computing is impossible if you cannot connect to the

Internet.

• Since you use the Internet to connect to both your

applications and documents, if you do not have an Internet

connection you cannot access anything, even your own

documents.

• A dead Internet connection means no work and in areas

where Internet connections are few or inherently unreliable,

this could be a deal-breaker.



• Does not work well with low-speed connections: • Similarly, a low-speed Internet connection, such as that

found with dial-up services, makes cloud computing painful at best and often impossible.

• Web-based applications require a lot of bandwidth to download, as do large documents.

• Features might be limited: • This situation is bound to change, but today many web-

based applications simply are not as full-featured as their desktop-based applications. • For example, you can do a lot more with Microsoft PowerPoint than

with Google Presentation's web-based offering



• Can be slow:

• Even with a fast connection, web-based applications can

sometimes be slower than accessing a similar software

program on your desktop PC.

• Everything about the program, from the interface to the

current document, has to be sent back and forth from your

computer to the computers in the cloud.

• If the cloud servers happen to be backed up at that moment,

or if the Internet is having a slow day, you would not get the

instantaneous access you might expect from desktop

applications.



• Stored data might not be secure:

• With cloud computing, all your data is stored on the cloud.

• The questions is How secure is the cloud?

• Can unauthorised users gain access to your confidential data?

• Stored data can be lost:

• Theoretically, data stored in the cloud is safe, replicated across

multiple machines.

• But on the off chance that your data goes missing, you have no

physical or local backup.

• Put simply, relying on the cloud puts you at risk if the cloud lets you

down.


Data Warehousing Unit-8 Currrent Development

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57 57

Which are our lowest/highest margin customers ?

Who are my customers and what products are they buying?

Which customers are most likely to go to the competition ?

What impact will new products/services have on revenue and margins?

What product prom- -otions have the biggest impact on revenue?

What is the most effective distribution channel?

A producer wants to know….


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58

Data, Data everywhere

yet ... • I can’t find the data I need

• data is scattered over the network

• many versions, subtle differences

I can’t get the data I need

need an expert to get the data

I can’t understand the data I found

available data poorly documented

I can’t use the data I found

results are unexpected

data needs to be transformed from one form to other

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What is a Data Warehouse?

A single, complete and

consistent store of data

obtained from a variety of

different sources made

available to end users in a

what they can understand and

use in a business context.

[Barry Devlin]


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What are the users saying...

• Data should be integrated across

the enterprise

• Summary data has a real value to

the organization

• Historical data holds the key to

understanding data over time

• What-if capabilities are required


61

What is Data Warehousing?

A process of transforming

data into information and

making it available to users

in a timely enough manner to

make a difference

[Forrester Research, April 1996]

Data

Information


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Evolution

• 60’s: Batch reports • hard to find and analyze information

• inflexible and expensive, reprogram every new request

• 70’s: Terminal-based DSS and EIS (executive information systems) • still inflexible, not integrated with desktop tools

• 80’s: Desktop data access and analysis tools • query tools, spreadsheets, GUIs

• easier to use, but only access operational databases

• 90’s: Data warehousing with integrated OLAP engines and tools


63

Warehouses are Very Large

Databases 35%

30%

25%

20%

15%

10%

5%

0% 5GB

5-9GB

10-19GB 50-99GB 250-499GB

20-49GB 100-249GB 500GB-1TB

Initial

Projected 2Q96

Source: META Group, Inc.

Resp

ondents


64

Very Large Data Bases

• Terabytes -- 10^12 bytes:

• Petabytes -- 10^15 bytes:

• Exabytes -- 10^18 bytes:

• Zettabytes -- 10^21 bytes:

• Zottabytes -- 10^24 bytes:

Walmart -- 24 Terabytes

Geographic Information Systems

National Medical Records

Weather images

Intelligence Agency Videos


65

Data Warehousing -

It is a process

• Technique for assembling and

managing data from various sources

for the purpose of answering business

questions. Thus making decisions that

were not previous possible

• A decision support database

maintained separately from the

organization’s operational database


66

Data Warehouse

• A data warehouse is a

• subject-oriented

• integrated

• time-varying

• non-volatile

collection of data that is used primarily in

organizational decision making.

-- Bill Inmon, Building the Data Warehouse 1996


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Data Mining Unit-8 Currrent Development

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Data mining

• Process of semi-automatically analyzing large databases to

find patterns that are:

• valid: hold on new data with some certainty

• novel: non-obvious to the system

• useful: should be possible to act on the item

• understandable: humans should be able to interpret the pattern

• Also known as Knowledge Discovery in Databases (KDD)

72


Why Data Mining • Credit ratings/targeted marketing:

• Given a database of 100,000 names, which persons are the least likely to default on their credit cards?

• Identify likely responders to sales promotions

• Fraud detection

• Which types of transactions are likely to be fraudulent, given the demographics and transactional history of a particular customer?

• Customer relationship management:

• Which of my customers are likely to be the most loyal, and which are most likely to leave for a competitor? :

Data Mining helps extract such information 73


Applications • Banking: loan/credit card approval • predict good customers based on old customers

• Customer relationship management: • identify those who are likely to leave for a competitor.

• Targeted marketing: • identify likely responders to promotions

• Fraud detection: telecommunications, financial transactions • from an online stream of event identify fraudulent events

• Manufacturing and production: • automatically adjust knobs when process parameter changes

74


Applications (continued)

• Medicine: disease outcome, effectiveness of treatments • analyze patient disease history: find relationship

between diseases

• Molecular/Pharmaceutical: identify new drugs

• Scientific data analysis: • identify new galaxies by searching for sub clusters

• Web site/store design and promotion: • find affinity of visitor to pages and modify layout

75


The KDD process

• Problem fomulation

• Data collection

• subset data: sampling might hurt if highly skewed data

• feature selection: principal component analysis, heuristic search

• Pre-processing: cleaning

• name/address cleaning, different meanings (annual, yearly), duplicate removal, supplying missing values

• Transformation:

• map complex objects e.g. time series data to features e.g. frequency

• Choosing mining task and mining method:

• Result evaluation and Visualization:

Knowledge discovery is an iterative process

76


Relationship with other fields

• Overlaps with machine learning, statistics, artificial

intelligence, databases, visualization but more stress

on

• scalability of number of features and instances

• stress on algorithms and architectures whereas foundations

of methods and formulations provided by statistics and

machine learning.

• automation for handling large, heterogeneous data

77


Some basic operations

• Predictive:

• Regression

• Classification

• Collaborative Filtering

• Descriptive:

• Clustering / similarity matching

• Association rules and variants

• Deviation detection

78


Data Mining in

Practice

79


Application Areas

Industry Application

Finance Credit Card Analysis

Insurance Claims, Fraud Analysis

Telecommunication Call record analysis

Transport Logistics management

Consumer goods Promotion analysis

Data Service providers Value added data

Utilities Power usage analysis


Why Now? • Data is being produced

• Data is being warehoused

• The computing power is available

• The computing power is affordable

• The competitive pressures are strong

• Commercial products are available

81


Data Mining works with

Warehouse Data

• Data Warehousing provides the

Enterprise with a memory

ÑData Mining provides the Enterprise with intelligence


Usage scenarios

• Data warehouse mining: • assimilate data from operational sources

• mine static data

• Mining log data

• Continuous mining: example in process control

• Stages in mining: • data selection pre-processing: cleaning

transformation mining result evaluation visualization

83


Mining market

• Around 20 to 30 mining tool vendors • Major tool players: • Clementine, • IBM’s Intelligent Miner, • SGI’s MineSet, • SAS’s Enterprise Miner.

• All pretty much the same set of tools • Many embedded products: • fraud detection: • electronic commerce applications, • health care, • customer relationship management: Epiphany

84


Green Computing Unit-8 Currrent Development

85

Green Computing


86

The positive (or least negative) relationship between the

physical computer and its impact to the environments in

which it moves through from cradle to grave

Cradle to Grave Approach

• Full life-cycle analysis, not just the product on our desks

• Looks at:

• Manufacturing

• Use during lifetime

• Disposal and reallocation

Green Computing • Why • computer energy is often wasteful • leaving the computer on when not in use (CPU and fan consume power,

screen savers consume power)

• printing is often wasteful • how many of you print out your emails or meeting agendas

• printing out partial drafts

• for a “paperless” society, we tend to use more paper today than before computer-prevalence

• pollution • manufacturing techniques

• packaging

• disposal of computers and components

• toxicity • as we will see, there are toxic chemicals used in the manufacturing of

computers and components which can enter the food chain and water! 87


Energy Use of PCs • CPU uses 120 Watts

• CRT uses 150 Watts • 8 hours of usage, 5 days a week = 562 KWatts • if the computer is left on all the time without proper power saver

modes, this can lead to 1,600 KWatts

• for a large institution, say a university of 40,000 students and faculty, the power bill for just computers can come to $2 million / year

• Energy use comes from • electrical current to run the CPU, motherboard, memory

• running the fan and spinning the disk(s)

• monitor (CRTs consume more power than any other computer component)

• printers

88


Chemical Elements Found in Computers and Components

• Elements in bulk: lead, tin, copper, silicon, carbon, iron and aluminum

• Elements in small amounts: cadmium and mercury

• Elements in trace amounts: • germanium, gallium, barium, nickel, tantalum, indium, vanadium, terbium,

beryllium, gold, europium, titanium, ruthenium, cobalt, palladium, manganese, silver, antimony, bismuth, selenium, niobium, yttrium, rhodium, platinum, arsenic, lithium, boron, americium

• List of examples of devices containing these elements • almost all electronics contain lead & tin (as solder) and copper (as wire &

PCB tracks), though the use of lead-free solder is now spreading rapidly

• lead: solder, CRT monitors (Lead in glass), Lead-acid battery

89


List Continued

• List of examples of devices containing these elements • tin: solder

• copper: copper wire, printed circuit board tracks

• aluminum: nearly all electronic goods using more than a few watts of power

• iron: steel chassis, cases & fixings

• silicon: glass, transistors, ICs, Printed circuit boards.

• nickel & cadmium: nickel-cadmium rechargeable batteries

• lithium: lithium-ion battery

• zinc: plating for steel parts

• gold: connector plating, primarily in computer equipment

• mercury: fluorescent tubes (numerous applications), tilt switches (pinball games, mechanical doorbells)

• sulphur: lead-acid battery

• carbon: steel, plastics, resistors

90


Disposal • Reuse: donate your computer components to people who

may not have or have lesser quality computers • inner city schools, churches, libraries, third world countries • this however leads to the older computers being dumped but there is

probably no way around this as eventually the older computers would be discarded anyway

• Refurbish: rather than discarding your computer when the next generation is released, just get a new CPU and memory chips – upgrade rather than replace • while you will still be discarded some components, you will

retain most of the computer system (e.g., monitor, the system unit housing, cables)

• Are there adequate incentives to do either of the above? Do computer companies encourage refurbishing/upgrading?

91


One More Solution: Recycling

• If companies can recycle the plastics and other

components, this can greatly reduce waste and toxins

• however, the hazardous materials in e-waste can harm the

recycle workers if they are not properly protected

• in undeveloped countries, a lot of the recycling chores are left up to

unprotected children!

• Developed countries now have facilities for recycling e-

waste

• however, in Europe, the plastics are discarded instead of

recycled because the flame retardant chemicals are too toxic to

work with

• To resolve these problems, the computer manufacturers

must start using recyclable chemicals 92


How Do the Companies Rate? • 8: Nokia - regained its top position for eliminating the

worst chemicals from many products

• still needs to report on its recycling rate percentage

• 7.3: Dell - still among the top but loses points for not

having models free of the worst chemicals

• strong support for global take back

• 7.3: Lenovo - dropping down the rank for not having a

clear global take back program

• still missing out on products free of the worst chemicals on the

market

• 7: Sony Ericsson - among the top with clear timeline to

have products free of the worst chemicals by 2008

• need better chemicals take back reporting program

93


Continued

• 6.7: Samsung - strong position for having a good chemical policy, but still lack products that are free from the worst chemicals • its take back system is not yet global and need improvement

• 6.7: Motorola - some products on the market are free from the worst chemicals but loses points for not providing clear timelines for eliminating these chemicals in all products • score points on reporting the recycling rate

• 6: Toshiba - good improvement particularly on waste and take back criteria • moved forward for providing some models without the worst

chemicals and for timelines for complete phase out

• 6: Fujitsu-Siemens - some models free of worst chemicals, but loses point for a weak take back and recycling program

94


Continued • 5.7: Acer - standing still with improved chemical policies but no

models free of the worst chemicals • needs to improve on take back program

• 5.3: Apple - top mover with concrete timelines to eliminate the worst chemicals • loses points for not have a green product on the market and for a weak take

back program

• 5.3: HP - a free-faller, dropping down for failing to provide clear timelines for eliminating the worst chemicals • it looses points for weak definition of take back policies

• 5: Panasonic - moving up for making available products free of the worst chemicals • loses point for poor take back program

• 4: Sony - at the bottom of the rank for losing penalty point for inconsistent take back policies • some models without the worst chemicals

95


Wireless Sensor Network Unit-8 Currrent Development

96

Introduction-WSN • Wireless Sensor Networks are networks that

consists of sensors which are distributed in an ad hoc manner.

• These sensors work with each other to sense some physical phenomenon and then the information gathered is processed to get relevant results.

• Wireless sensor networks consists of protocols and algorithms with self-organizing capabilities.

97


Example of WSN

98


Ref:http://esd.sci.univr.it/images/wsn-example.png

http://esd.sci.univr.it/images/wsn-example.png



Comparison with ad hoc

networks

• Wireless sensor networks mainly use broadcast communication

while ad hoc networks use point-to-point communication.

• Unlike ad hoc networks wireless sensor networks are limited by

sensors limited power, energy and computational capability.

• Sensor nodes may not have global ID because of the large

amount of overhead and large number of sensors.

99


Applications of Wireless Sensor

networks

The applications can be divided in three categories:

1. Monitoring of objects.

2. Monitoring of an area.

3. Monitoring of both area and objects.

* Classification due to Culler, Estrin, Srivastava

100


Monitoring Area

• Environmental and Habitat Monitoring

• Precision Agriculture

• Indoor Climate Control

• Military Surveillance

• Treaty Verification

• Intelligent Alarms

101


Example: Precision

Agriculture

• Precision agriculture aims at making cultural operations more efficient, while reducing

environmental impact. • The information collected from

sensors is used to evaluate optimum sowing density, estimate fertilizers and other inputs needs, and to more accurately predict crop yields.


Monitoring Objects

• Structural Monitoring

• Eco-physiology

• Condition-based Maintenance

• Medical Diagnostics

• Urban terrain mapping

103


Example: Condition-based

Maintenance

• Intel fabrication plants

• Sensors collect vibration data, monitor wear and

tear; report data in real-time

• Reduces need for a team of engineers; cutting costs

by several orders of magnitude

104


Monitoring Interactions between Objects and

Space

• Wildlife Habitats

• Disaster Management

• Emergency Response

• Ubiquitous Computing

• Asset Tracking

• Health Care

• Manufacturing Process Flows

105


Example: Habitat

Monitoring

• The ZebraNet Project

Collar-mounted sensors monitor zebra movement in

Kenya

Source: Margaret Martonosi, Princeton University 106


Characteristics of Wireless

Sensor Networks • Wireless Sensor Networks mainly consists of sensors.

Sensors are -

• low power

• limited memory

• energy constrained due to their small size.

• Wireless networks can also be deployed in extreme environmental conditions and may be prone to enemy attacks.

• Although deployed in an ad hoc manner they need to be self organized and self healing and can face constant reconfiguration.

107


Design Challenges

• Heterogeneity

• The devices deployed maybe of various types and need to

collaborate with each other.

• Distributed Processing

• The algorithms need to be centralized as the processing is

carried out on different nodes.

• Low Bandwidth Communication

• The data should be transferred efficiently between sensors

108


Continued..

• Large Scale Coordination

• The sensors need to coordinate with each other to produce required results.

• Utilization of Sensors

• The sensors should be utilized in a ways that produce the maximum performance and use less energy.

• Real Time Computation

• The computation should be done quickly as new data is always being generated.

109


Operational Challenges of Wireless

Sensor Networks

• Energy Efficiency

• Limited storage and computation

• Low bandwidth and high error rates

• Errors are common • Wireless communication

• Noisy measurements

• Node failure are expected

• Scalability to a large number of sensor nodes

• Survivability in harsh environments

• Experiments are time- and space-intensive

110


Enabling Technologies

Embedded Networked

Sensing

Control system w/

Small form factor

Untethered nodes

Exploit

collaborative

Sensing, action

Tightly coupled to physical world

Embed numerous distributed

devices to monitor and interact

with physical world

Network devices to coordinate and

perform higher-level tasks

Exploit spatially and temporally dense, in situ, sensing and actuation 111


Future of WSN Smart Home / Smart Office

• Sensors controlling

appliances and electrical

devices in the house.

• Better lighting and

heating in office

buildings.

• The Pentagon building

has used sensors

extensively. 112


Biomedical / Medical

• Health Monitors

• Glucose

• Heart rate

• Cancer detection

• Chronic Diseases

• Artificial retina

• Cochlear implants

• Hospital Sensors

• Monitor vital signs

• Record anomalies 113


Industrial & Commercial

• Numerous industrial and commercial applications:

• Agricultural Crop Conditions

• Inventory Tracking

• In-Process Parts Tracking

• Automated Problem Reporting

• RFID – Theft Deterrent and Customer Tracing

• Plant Equipment Maintenance Monitoring

114


Traffic Management & Monitoring

Future cars could use wireless sensors to:

Handle Accidents

Handle Thefts

Sensors embedded in the roads to:

–Monitor traffic flows

–Provide real-time route updates

115



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