rental home system for nearest place prediction · rental home system for nearest place prediction...

10
RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1 , K.Mounika 2 , S.Muthu Subhashini 3 , S.Suganthi 4 1 Assistant Professor, Department of Computer Science and Engineering , Karpagam College of Engineering, Coimbatore. 2,3,4 Student, Department of Computer Science and Engineering, Karpagam College of Engineering, Coimbatore. ABSTRACT We propose to rented home system with java script technology for users. User can search rented home in various places like district wise and local area wise With the current paradigm shift in technological field, there is an urgent need to embrace and appreciate the power of technology. Housing sector remains vigilant to face the challenges of change by employing a new strategy that facilitates easy management of rental houses. Distance vector routing protocols have been widely adopted as an efficient routing mechanism in current Internet, and many wireless networks. However, as is well-known, the existing distance vector routing protocols are insecure as it lacks of effective authorization mechanisms and routing updates aggregated from other routers. As a result, the network routing- based attacks become a critical issue which could lead to a more deteriorate performance than other general network attacks. Hence there is need to develop a rental house management system that can simplify work for the rental managers so that all their work can be efficient and effective. To get information about how rental houses are currently being managed, the user input values and submitted to server. the server manage the number of rental house information. Keywords: location prediction, house quality, vacant place, distance vector algorithm (DVA). I.INTRODUCTION Rental Home Management System are to Ensure all rental housing exceeds adopted minimum housing quality standards through systematic code enforcement. Encourage a range of affordable, accessible, and decent rental housing options throughout the community. Consider expanding the use of housing preservation programs whenever appropriate. Encourage participation in and use of low-interest rehabilitation and home purchase loan funds. Promote International Journal of Pure and Applied Mathematics Volume 119 No. 10 2018, 1677-1686 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu 1677

Upload: others

Post on 30-Apr-2020

6 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

RENTAL HOME SYSTEM FOR NEAREST PLACE

PREDICTION

R. Nandhini1, K.Mounika2, S.Muthu Subhashini3, S.Suganthi4

1Assistant Professor, Department of Computer Science and Engineering , Karpagam College

of Engineering, Coimbatore.

2,3,4Student, Department of Computer Science and Engineering, Karpagam College of

Engineering, Coimbatore.

ABSTRACT

We propose to rented home

system with java script technology for

users. User can search rented home in

various places like district wise and local

area wise With the current paradigm shift

in technological field, there is an urgent

need to embrace and appreciate the power

of technology. Housing sector remains

vigilant to face the challenges of change

by employing a new strategy that

facilitates easy management of rental

houses. Distance vector routing protocols

have been widely adopted as an efficient

routing mechanism in current Internet, and

many wireless networks. However, as is

well-known, the existing distance vector

routing protocols are insecure as it lacks of

effective authorization mechanisms and

routing updates aggregated from other

routers. As a result, the network routing-

based attacks become a critical issue

which could lead to a more deteriorate

performance than other general network

attacks. Hence there is need to develop a

rental house management system that can

simplify work for the rental managers so

that all their work can be efficient and

effective. To get information about how

rental houses are currently being managed,

the user input values and submitted to

server. the server manage the number of

rental house information.

Keywords: location prediction, house

quality, vacant place, distance vector

algorithm (DVA).

I.INTRODUCTION

Rental Home Management System are to

Ensure all rental housing exceeds adopted

minimum housing quality standards

through systematic code enforcement.

Encourage a range of affordable,

accessible, and decent rental housing

options throughout the community.

Consider expanding the use of housing

preservation programs whenever

appropriate. Encourage participation in

and use of low-interest rehabilitation and

home purchase loan funds. Promote

International Journal of Pure and Applied MathematicsVolume 119 No. 10 2018, 1677-1686ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

1677

Page 2: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

adaptive reuse of existing vacant or under-

utilized structures, such as convents,

schools, and industrial buildings, into

housing with an affordable and/or

workforce component, where appropriate.

Encourage the expansion of the capacity of

neighbourhood associations. Promote

residential educational workshops

regarding restoration, rehabilitation, and

maintenance. Encourage relocation of

existing housing as opposed to demolition

whenever possible; when removal is

necessary, require deconstruction and

landfill diversion as much as possible

Promote historic preservation as the

cornerstone of housing and neighbourhood

revitalization programs, to promote

economic development and attract younger

residents.

Improve and prepare the home for rent - A

property manager will suggest and oversee

cosmetic improvements that maximize

revenue.

Determine the best rent rate - Too high and

you are stuck waiting, to low and you’re

losing money every month the tenant is in

the unit. Determining the optimal price

requires knowledge of the local market,

data on recently sold comparables, and

access to rental rate tool .Effectively

market your home . An experienced

property management company has

written hundreds of ads and understands

what to say and where advertise in order to

get larger pool of candidates in a shorter

period of time. Additionally because of

their volume they can usually negotiate

cheaper advertising rates both online and

offline.

II.PROBLEM STATEMENT

In our day-to-day life, buyer’s face a lot

of issues related to household such as

reporting an issue, tracking the location

and receiving necessary information

instantly etc.., and similarly seller’s also

deal with issues such as keeping track of

issues in apartments, notifying that a

package has arrived, sending emergency

information quickly to the buyers etc.

Currently there is no app which focuses on

to resolve this particular issue. The

existing app help to solve the issue but not

in an effective manner. To help overcome

the problems faced by buyers and sellers, a

new app is developed. This app focuses on

to build a better relationship between

buyers and sellers by simplifying many

tasks such as sending automatic rent

reminders, package notifications, utilities

bill, emergency info, location information,

documents and sharing issues.

III.RELATED WORK

Rental house management has become

important factor in modern society hence

the need to have a rental house

International Journal of Pure and Applied Mathematics Special Issue

1678

Page 3: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

management system[3]. This chapter will

provide a brief understanding about

background of study, definition of the

project problem statement, its objectives,

scopes, project justification, risks, project

deliverables and project budget and

schedule. Housing has a central

importance to quality of life with

considerable economic, social, cultural and

personal significance. Though a country’s

national prosperity is usually measured in

economic terms, increasing wealth is of

diminished value unless all can share its

benefits and if the growing wealth is not

used to redress growing social

deficiencies, one of which is housing

(Erguden,2001). Housing plays a huge role

in revitalizing economic growth in any

country, with shelter being among key

indicators of development. The universal

declaration of human rights gives one of

the basic human rights as the right to a

decent standard of living, central to which

is the access to adequate housing (United

Nations, The Human Rights-article 25,

1948)[7]. Housing as a basic human right

demands that urban dwellers should have

access to a decent housing, defined as one

that provides a foundation for rather than

being a barrier to good physical and

mental health, personal development and

fullfillment of life objectives (Seedhouse,

1986). The focus of this research project is

basically managing housing for low

income, medium and high incomes

households or what is commonly known as

affordable housing. „Affordable‟ is a

term used to describe individuals‟

capability to pay for certain products or

services because their income is enough to

do so. Although the term „affordable

housing‟ is often applied to rental

housing; that is within the financial means

of those in the lower income ranges of a

geographical area, the concept is

applicable to both middle and high income

individuals[5]. Most families choose to

rent houses based on their income and

family situations; unfortunately, there may

not be enough good quality rental housing

for these families. Housing is a major

problem in Kenya especially in Nairobi

city. Millions of people are living in

sprawling slams and also in other informal

settlement around Nairobi (UN-Habitat,

2008). This explains why many people

have shifted their focus to developing

rental houses in Nairobi and other parts of

the country[9]. The demand for rental

houses is extremely high and more rental

houses need to be put in place. Developing

rental houses comes with many advantages

especially to the Landlords who are able to

increase their profits through rent paid by

the tenants. Increased number of tenants

and Landlords makes management

difficult especially for the landlords who

are losing huge sum of money through

International Journal of Pure and Applied Mathematics Special Issue

1679

Page 4: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

tenants who evade rent. The above

statement gives a clear declaration as to

why rental house management system

need to be developed.

IV.PROBLEM WITH EXISTING

SYSTEM

Currently the most property managers

manage property and tenants details on

papers. Once customers finds a vacant

house, they can call or email manager of

the houses indicating the size of the house

they would like rented to them. The

property manager can email them back

giving them all the details about the house

they are requesting. The details include;

Rent per month Deposit paid Terms and

conditions to follow acceptance.

With the current system recording the

details of various activities of user is

completely manual and entails a lot of

paper work. Each house has a file that

contains the house: number, size, rent per

month, expected deposit, occupant and

status. Rent payment table contains

tenants: first name, last name, Phone

number, date of payment, amount and

balance if any. The existing system only

provides text based interface which is not

as user friendly as Graphical user

interface. Since the system is implemented

manually, the response is very slow. The

transactions are not secure as papers may

get lost or damaged. Hence, there is need

of reformation of the system with more

advantages and flexibility. The system

eliminates most of the limitations of the

existing system.

V.PROPOSED SYSTEM

User initially want to sign up and create

the account and user logs in the system

automatically will show number of rented

house in particular places. In this

information like owner name ,house rent,

address, and mobile number will the user

to avoid the house broker, rent payment

form, registration form. Each form has

several command buttons like new, search,

cancel, Back and exit. With the command

buttons you can manipulate the database.

If you want to add data to the database all

you need to do is to click on new then

input data in the textboxes provided then

click save and the data will automatically

be saved. If you want to view data in the

database you just click Search button and

the data will be displayed for you.. You

may enter data then decide to cancel it, it

is simple click on cancel and it will be

canceled. further ,with this location also

available. Picture of the places will be

uploaded daily to the seller. The buyer can

subscribe the needed location so he/she

will receive the notification if any

updation of homes occurred in the required

International Journal of Pure and Applied Mathematics Special Issue

1680

Page 5: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

place. If buyer has any queries he/she can

contact us through customer care service

option provided in this app. The queries

will be rectified with in one week.

Using Distance vector algorithm, we

present the security mechanism including

the message exchange and update

message security authentication

mechanism. The suggested approach

shows that the security mechanism can

effectively verify the integrity and

validate the freshness of routing update

messages received from neighbor nodes.

In comparison with exiting mechanisms

(SDV, S-RIP etc), the proposed model

provides enhanced security without

introducing significant network overheads

and complexity.The classical Bellman-

Ford algorithm is used for computing

shortest paths between any two given

nodes in a graph. The distributed version

of this algorithm (DBF) was the origin of

most of the distance-vector routing

algorithms and protocols used today.

VI.CONCLUSION

Effectively resolving the apartment issues

is important to the buyer's long-term

future, the Rental Property Management

app will be an important tool for creating

rental housing stability by helping tenants

speak with greater credibility through

initiating and documenting

communications and building productive

relationships with sellers. Rental property

management provides buyers of specific

housing associations and social sellers

International Journal of Pure and Applied Mathematics Special Issue

1681

Page 6: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

with a simple way to report and arrange

repairs to properties. Finally, the goal of

the app is to create a better relationship

between tenants and a sellers which can be

achieved through this app.

VII.FUTURE WORK

In future our project is meant to satisfy

the needs of rental house owners.

Several user friendly interfaces have

also been adopted. This package shall

prove to be a powerful in satisfying all

the requirements of the users It is with

utmost faith that I present this software

to you hoping that it will solve your

problems and encourage you to continue

appreciating technology because it is

meant to change and ease all our work

that seems to be very difficult. I don't

mean that my project is the best or

that I have used the best technology

available it just a simple and a humble

venture that is easy to understand .In

extent we can add GPS system in build

and can give live chat online option to

users. This app can also be extended to

iOS Platform and several state Database

can be included. Could also allow local

business to push deals/coupons within a

certain geographic area.

VIII.REFERENCES

[1] Ambrose, P. and Barlow, J. (1987),

Housing Provision and House Building in

Western Europe: Increasing Expenditure,

Declining Output, Housing Markets and

Policies under Fiscal Austerity, London,

Greenwood Press.

[2] Cooper, M. (1998), Ideas to develop a

literature review, vol. 3, page, 39.

[3] Erguden , S. (2001), Low cost housing

policies and constraints in developing

countries, International conference on

spatial development for sustainable

development, Nairobi.

[4] Golland , A. (1996), Housing supply,

profit and housing production: The case of

the United Kingdom, Netherlands and

Germany, Journal of Housing and the Built

Environment, vol.11, no1.

[5] Hancock, T. (1998), Caveat partner:

Reflection of Partnership with the private

sector, Health promotion international, vol.

13, no 3

[6] Priya Gupta, 2 Surendra Sutar,

“Multiple Targets Detection And Tracking

System For Location Prediction”,

International Journal of Innovations in

Scientific and Engineering Research

(IJISER), Vol.1, No.3, pp.127-130,2014.

[7] Levin, K. (1999), Database

Management Systems: How to use

Relational Databases, vol. 2, no 4.

International Journal of Pure and Applied Mathematics Special Issue

1682

Page 7: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

[8] Macoloo, G. (1994), The changing

nature of financing low income urban

housing development in Kenya, Housing

Studies, vol. 9, Issue 2, pages 189281.

[9] Mitullah, W. (2003), Urban Slums

Report: The case of Nairobi Kenya,

Understanding Slums: Case Studies for the

Global Report on Human Settlements.

[10] Seedhouse, D. (1986), Foundation for

Health Achievement, Health Policy, vol. 7,

issue, 3.

[11] United Nations, (1948), The Bill of

Human Rights.

[12] http://www.ehow.com

[13] Bellovin S.M. Security problems in

the TCP/IP protocol suite. Comput

Commun Rev, 1989, 19: 32–48

[14] Kuo C F, Pang A C, Chan S K.

Dynamic routing with security

considerations. IEEE Trans Parallel

Distrib Syst, 2009, 20: 48–58

[15] He L. Recent developments in

securing Internet routing protocols. BT

Technol J, 2006, 24: 180–196

[16] Lakshminarayanan K, Caesar M,

Rangan M, et al. Achieving convergence-

free routing using failure-carrying packets.

In: ACM SIGCOMM 2007. New York:

ACM Press, 2007. 241–252

[17] Wang B, Guo Y F, Lan J L, et al.

Fast network self-healing mechanism

based on distance vector routing protocol.

J Internet Technol, 2010, 11: 659–667

[18] Kim H, Shin G. On predictive

routing of security contexts in an all- IP

network. Secur Commun Netw, 2010, 3:

4–15

[19] Rick K, Simon L, Hart R. Practical

interdomain routing security. IT Prof,

2009, 11: 54–56

[20] Jun L, Brooks S. I-seismograph:

Observing and measuring Internet

earthquakes. In: IEEE INFOCOM 2011.

Washington: IEEE Computer Society,

2011. 2624–2632

[21] Bellman R. On a routing problem. Q

Appl Math, 1958, XVI: 87–90

[22] Yi Q, James J, David T, et al.

Information Assurance: Dependability

and Security in Networked Systems. San

Fransisco: Morgan Kaufmann Publishers,

2007

[23] Haim Z, Levy H. Area avoidance

routing in distance-vector networks. In:

Proc of IEEE INFOCOM. Washington:

IEEE Computer Society, 2008. 475–483

[24] Mittal V, Vigna G. Sensor-based

intrusion detection for intra-domain

International Journal of Pure and Applied Mathematics Special Issue

1683

Page 8: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

distance-vector routing. In: Proc of

CCS'02. Washington: IEEE Computer

Society, 2002. 127–137

[25] Hu Y C, Perrig A, Johnson D B.

Efficient security mechanisms for routing

protocols. In: Proc NDSS'03. San Diego:

IEEE Computer Society, 2003. 1–17

[26] Tao W, Kranakis E, Oorschot P. S-

RIP: A secure distance vector routing

protocol. In: Proc of 2006 Securecomm

and Workshops. Washington: IEEE

Computer Society, 2006. 103–109

[27] Babakhouya A, Challal Y,

Bouabdallah M, et al. SDV: A new

approach to secure distance vector

routing protocols. In: Proc of 2006

Securecomm and Workshops.

Washington: IEEE Computer Society,

2006. 1–10

[28] Sheng B, Wang H N, Pan J P.

Keychain-based signatures for securing

BGP. IEEE J Sel Areas Commun, 2010,

28: 1308–1318

[29] Neven G. Efficient sequential

aggregate signed data. IEEE Trans Inf

Theory, 2011, 57: 1803–1815

International Journal of Pure and Applied Mathematics Special Issue

1684

Page 9: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

International Journal of Pure and Applied Mathematics Special Issue

1685

Page 10: RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION · RENTAL HOME SYSTEM FOR NEAREST PLACE PREDICTION R. Nandhini 1, K.Mounika 2, S.Muthu Subhashini 3, S.Suganthi 4 1Assistant Professor,

1686