1. BY S.PRISCILLA STEFFI

2.  Till now online communication involved only two of our senses.  SENSE OF SIGHT  SENSE OF HEARING  A new technology targets on sense of smell WHAT IS DIGITAL SCENT TECHNOLOGY ?  Digital Scent Technology intends to change the interactive entertainment experience.  Using Electronic-nose we can sense a smell and Digital scent technology it is possible to sense, transmit and receive smell through internet.

3. PHYSIOLOGICAL ASPECTS OF SMELL  Smell is most evocative of senses.  How does the nose work?  Odour.  Olfactory mucosa and Olfactory bulb.  Primary odours

4. WHAT IS AN ELECTRONIC NOSE ?  Electronic nose is a device which detects odour and analyze it. MAIN COMPONENTS  Sensing system  Pattern recognition system SUB COMPONENTS  Sample delivery system  Detection system  Computing system

5. ANALOGY BETWEEN THE ELECTRONIC NOSE AND BIOLOGICAL NOSE BIOLOGICAL NOSEELECTRONIC NOSE InhalingPump Mucus Filter Olfactory EpitheliumSensors Binding With ProteinsInteraction Cell Membrane Depolarized Signal Nerve ImpulsesCircuitry & Neural Network

6. SENSORS USED IN ELECTRONIC NOSE  What is a sensor ?  Sensor quality  Binding with Proteins TYPES OF SENSORS  Polymer sensors  MOS sensors  MOSFET sensors  Quartz sensors  Acoustic sensors  Optical fibre sensors

7. POLYMER SENSORS  16 different polymer films  Fixed voltage  Change in conductivity of the polymer  Base line resistance  Bacterial Vaginosis (Bv) MOS SENSORS  Semiconducting film  Taughi and Figaro  n-type and p-type semiconductors  Thick and thin film material  200 o C to 400 o C  Detect gas leakage, combustible and toxic gases

8. DATA ANALYSIS : PATTERN CLASSIFICATION  3-dimensional output matrix ( X ij (t) )  Response matrix R = X 11 X 12....X 1m X 21 X 22....X 2m.....X ij.... X n1 X n2....X nm PRE-PROCESSING DATA ANALYSIS  Baseline manipulation (X ij odor - X i 0 ) / X i 0  Compression of data  Normalization

9. MULTIVARIATE DATA ANALYSIS PARC engine can be classified into  Parametric  Non- parametric  Supervised  Non- supervised VARIOUS ANALYSIS  Linear discriminant analysis  Principal component analysis  Clustering analysis

10. LDA PCA Z p =a 1p X 1j + a 2p X 2 j +...............+ a ip X ij +..............+ a np X nj  Supervised Linear data reduction technique

11. CLUSTER ANALYSIS  unsupervised, non-parametric  data into multiple groups  K-clustering, Tree clustering ARTIFICIAL NEURAL NETWORS  Analyze complex and non-linear data  Artificial neurons  Multi layer perceptron

12.  E-nose detects the smell molecules  Scent is indexed according to its chemical make up  Scent spectrum  Scent synthesizer  Air cannon WHAT IS DIGITAL SCENT COMMUNICATION?

13. CARTRIDGES USED IN SCENT SYNTHESIZERS  19 types of smell creating chemicals.  19 partitions in the container  Anode, cathode and electrolyte  Chemical are derived from bacteria or plants SWEET SMELL OF SUCCESS  Scent stream  Scent Registry  Broad array of tools 

14.  Trisenx allows users to not only download scents, but to print out flavors that can be tasted  It is a printer like desktop device  Savannah, GA, based company  Aromas are stored in a disposable cartridge.  This cartridge has 20 chambers, each holding a distinct scent. Thousands of smells can be created with a 20-chamber cartridge SENX SCENT DEVICE (sensory enhanced net experience) WHAT IS SENX SAMPLER?  Effective diffusion of all available fragrances  Chemical compounds used in producing aroma aldehyde, esther,alcohol and ketones.

15. WHAT IS AN AIR CANNON?  Directs smell to user’s nose  Nose Tracker  Air clump launcher  Scent Generator  3 Prototypes

16. THIRD PROTYPE  A scent switching mechanism is provided  Sub chamber  Scent cartridge

17. SUMMARY  ELECTRONIC NOSE  SENSORS  DATA ANALYSIS  ISMELL PERSONAL SCENT SYNTHESIZERS  AIR CANNON

18. BIBLIOGRAPHY  http://nanotech.sc.mahidol.ac.th/nano/E-Nose.pdf  http://www.toodoc.com/Digital-Scent-Technology-ppt.html  http://www.trisenx.com/now.html  http://en.wikipedia.org/wiki/Metal_oxide_semiconductor  http://www.vecc.gov.in/~sacet09/downloads/INVITED%20SPEAK ER%20LECTURE/Nabarun.pdf  http://www.mdpi.com/1424-8220/9/8/6058/pdf

19. THANKYOU