The document proposes an indoor navigation system for malls using Wi-Fi signal strength. It would determine a user's position by calculating the intersection point of signal strengths from three access points. The system would find the shortest path between a user's location and destination using Dijkstra's algorithm on a graph of the mall's floorplan. The project aims to help users navigate inside large indoor spaces like malls and offices.

1. Indoor Navigation System for mall

2. System Requirement
• Net Beans
• Android Smartphone
Hardware requirements:
• PC with minimum
• 100mb space
• 1GHz processor
• 512mb RAM

3. Introduction
• In order to navigate within a building, one
must first determine one’s current location. In
this section, multiple positioning techniques
are described and they are compared in the
first section.
• Two factors of particular importance in the
consideration of positioning techniques are
accuracy and convergence time. These factors
should be for the case in which the device
determining the position is stationary and for
the case in which the device is moving.

4. 1. GPS
2. A-GPS
3. Pseudo lite GPS
4. Bluetooth
5. Wi-fi
Potential Technologies

5. Wireless Fidelity:
• Wireless Fidelity (Wi-Fi) uses IEEE 802.11
standard. Each wireless router broadcasts a signal
that is received by devices in the area. Wireless
devices have the capability to measure the
strength of this signal. This strength is converted
to a number, known as received signal strength
indicator (RSSI).
• RSSI is a dimensionless metric that is used by
systems to compare the strength of signals from
multiple access points. RSSI is converted to actual
signal strength using standard conversion values.

6. • Wi-Fi devices such as laptops and
smartphones typically perform this conversion
automatically in order to provide signal
strength information to applications running
on the device.
• An advantage of Wi-Fi is that wireless
networks are universal. They exist in
population-dense areas and are continuously
spreading outward. This causes Wi-Fi based
systems to have a lower cost of
implementation.

7. Potential Technologies Pros Cons
GPS • Moderate accuracy
• High availability
• Low to minimal indoor
accuracy
A-GPS • Moderate outdoor
accuracy
• Minimal indoor
accuracy
Pseudolite GPS • High indoor and
outdoor accuracy
• Very expensive
equipment
Bluetooth • Low power
• Low financial cost
• Moderate to low range
• High cost of
implementation
Wifi • Readily available
throughout most
buildings
• Minimal costs for
implementation
• Medium range
• Network strength can
vary due to multipath
propagation

8. • Our system proposes an indoor position
detection using Wi-Fi signal strength and a
formula to determine position of a user. Three
access points (AP) are needed in order to
determine the position of a user in an indoor
location.
• Wireless routers provide coverage of about 100
feet (30.5 meters), signal strength is used to find
the collision point in order to specify the accurate
position of an object.
• We assume the three APs are known as AP1, AP2,
and AP3.
Proposed System

9. Diagram:

10. • Then, based on three coordinates of the APs, we
need to find the coordinates of the user’s
position that is represented as Z.
• Let’s assume that a user is using a smart phones
that serves as a receiver of the signals
transmitted from the access points. Application
of Wi-Fi analyzer in the smart phone presents the
signal strength in terms of percentage. The
highest percentage of signal strength indicates
that Z is closest to the AP whereas the lowest
percentage implies that Z is maximum range of
AP.

11. • The percentage of signal strength obtained
from the Wi-Fi analyzer can be converted to
distance between a user’s to each AP using
this equation :
• Distance, di = p ( 1 – mi )
• Where;
• m = is the percentage of signal strength
• p = is the maximum coverage of signal
strength
• i = 1,2,3

12. Shortest Path
• Dijkstra’s algorithm is one of the most used routing
algorithm. This algorithm is suitable for problems
dealing with a single source node and one or more
destination nodes.
• The algorithm works by advancing a single node at a
time, starting from the source node. At each step
during the loop, the algorithm chooses a node that has
the minimum cost from the source node. This node has
been visited from the source and has not yet been
optimized. This node is then marked as optimized and
the cost to all the adjacent nodes will be evaluated.
• The optimized cost to the destination is found once the
algorithm reaches the destination nodes.

13. Dijkstra’s Bellman Ford A*
Pros • High Speed
• Optimal
• Optimal
• Work with
negative weight
• High Speed
Cons • Doesn’t work
with negative
graph
• Low Speed • Not always
optimal

14. Scope
• Can be implemented in multistory malls for
better navigation for guidance or movement
inside mall.
• This application will provide assistance to the
guest user for finding shortest path from their
location to the destination location.
• With few changes we would able to
implement this in offices, colleges, hospitals
for indoor navigation.

15. Wi-Fi
Wi-Fi Positioning
Navigation Routing
Interface
Graphical User Interface
User Interaction
Database Searching

16. Group Members
• Kishan Shirodkar
• Supresh Gaonkar
• Gaurish Paranjape