ENN591/ENN593 Project Report: Anti-Collision System in Healthcare

This project report, submitted for ENN591 and ENN593, investigates a smart healthcare anti-collision system designed to assist visually impaired individuals. The report explores the application of Radio Frequency Identification (RFID) and the Internet of Things (IoT) within healthcare settings, focusing on an indoor anti-collision alarm system. It delves into the challenges of implementing such a system, including issues related to data privacy, technical limitations, and management complexities. The report incorporates various management concepts, such as SWOT analysis, Pareto charts, and QFD, to analyze the system's effectiveness and identify potential areas for improvement. It also reviews the literature on smart healthcare and the use of RFID technology, discussing RSSI values and phase profiles for obstacle detection. The study proposes solutions to overcome these challenges, including the use of LWLR algorithms and fingerprint system designs. The report concludes with recommendations for enhancing the system's performance and usability, ultimately aiming to improve patient care and safety in healthcare environments. The report also touches on the need for smart healthcare systems through anti-collision alarm systems for the blind or poor eye-sighted patients, including the different management theories which have developed the smart Healthcare system and focused on the loopholes with better resolution.

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ENN591 and ENN593 Project
Master of Engineering Management (BN87)
Master of Professional Engineering (EN55)
Assessment Item 2: Final report

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Contents
Introduction......................................................................................................................................3
Background and contact for the investigation:............................................................................3
Management problem in terms of the Research question:...........................................................4
Aims and objectives:....................................................................................................................4
Outcomes and results achieved....................................................................................................5
Significance.................................................................................................................................5
Literature Review............................................................................................................................5
Management concepts...................................................................................................................12
1. SWOT ANALYSIS...................................................................................................................12
2. Several of Pareto charts, flow-charts, Gantt chart and check sheets, Ishikawa Diagram..........17
3. QFD house of quality.................................................................................................................26
Methods of application..................................................................................................................31
Recommendations and conclusion................................................................................................37
References:....................................................................................................................................39

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Introduction
In today's date, smart Healthcare is increasing and is applied in every hospital in Australia.
Healthcare is an essential part of life and emerging with Information Technology have improved
the efficiency of the organizations by reducing the pressure on the Healthcare system. A collision
avoidance system can be considered as a system software which has focused on the collision
warning system or mitigation system for preventing or reducing the severity of collision in the
health sector. In regards to the development of IOT, different technologies are applied to
impaired people especially for blind, elderly and patients with eye disease. This type of diseases
has emerged smart indoor anti-collision system in each and every hospital of Australia which
uses monitors or diploid sensors for providing outside information to them. The anti-collision
system for visually impaired people has attracted a huge blind and poor eye-sighted people in
entire Australia.
Background and contact for the investigation:
The study has focused on an anti-collision alarm system which is the first attempt for designing
and anti-collision system for the visually impaired people in Australia. It has also focused on the
management issue in the health department of Australia which also includes different
management approaches. Important management concepts were adopted in this study to
understand the relation between the anti-collision alarm system and Management in the
Australian health department. Few challenges were introduced in the study which was
unwrapped phase change and phase value for anti-collision detection (Xiao, et al. 2018).
Adoption of different management concepts was described and Along with this smart
Technology few recommendations were provided for the problems that are occurring.

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Management problem in terms of the Research question:
The treatment and the solution of health economic problem by using Management concept is a
permanent challenge. Adoption of smart Healthcare systems has focused on different complexity
in the management of the health sector. It has focused on the longsuffering data analyst which
resulted in the Care Management of the patient and has captured the activities for monitoring and
reporting the program performance. Few management problems that have been adopted in the
research study are:
 Intelligent care can be an issue for the life cycle of patients.
 Improved Technology can make the situation more Complex for the management in
terms of payment and admission (Zeng, et al. 2016)
 Absent Network and data of electronic health records can become a stressful situation for
the management to care for the patient.
Aims and objectives:
Aim of the project refers to the overall purpose of the study whereas the objective of the study is
to focus on the different accomplishment according to the visibility of the project. The aim and
objective also focus on the evaluation of the effectiveness with recovery opportunities in the
project (Stein, et al. 2017). This project has analyzed and investigated the different issues of the
management for the anti-collision alarm system which is implemented in the Healthcare
organization.
The study has focused on the following objectives and aim according to the research:
 Analyzing the different benefits of the smart system like IoT in Healthcare organization
of Australia.

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 Evaluating the different problems of IoT that were identified in implementing the smart
technology in the Healthcare of Australia.
 Applying different management concepts for analyzing the problem statement of the
project.
 Few recommendations with proper solutions for eradicating the issues.
Outcomes and results achieved
The different approaches and resolution in the study have focused on the challenges and issues
that matter emerging in the Healthcare sector. It has also focused on the anti-collision system
which has solved many problems that have visualized for impaired people including blind,
elderly and eyes disease people. Also, the study has highlighted the high accuracy and efficiency
in guiding the improvement in the quality care of patients. The approaches and proper resolution
have eliminated the management problem for adopting smart technologies in Healthcare.
Significance
The project has developed about the need of smart Healthcare system through anti-collision
alarm system for the blind or poor eye-sighted patients. It has also developed the different
management theories which have developed the smart Healthcare system and focused on the
loopholes with better resolution.
Literature Review
Concept of smart healthcare

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Smart Healthcare has tremendously attracted attention from the world calling for the integrated
design brought together with an interdisciplinary approach of Technology. It aims to support
high quality and affordable patient care. Researchers are currently making advances within their
studies of the next generation information technology applications like the internet of things,
fifth generation wireless networks, cloud radio access networks and others (Goetz, 2018). Smart
Healthcare carries the potential for revolutionizing several aspects in the society specifically for
the patients who are disabled. Previous literary works have generally improvised the idea of
using video monitors and deployed sensors in order to provide the outside environment with
information necessary for the visually impaired patients and also send the alarms wherever the
risk of different obstacles can be sensed. Another important application in daily life depends on
the traditional guide of anti-collision rod for avoiding obstructions created outside (Yonak,
2016). Eyeron-man can be regarded as the smart waste having sensors installed which takes
complete advantage of ultrasonic sensors infrared sensors and leisure editor for protecting the
visually impaired patients out of the risks from pre-deployed dangerous regions.Along with the
improvement in variable internet of things several Technologies have been applied into the daily
lives of people that bring smarter solutions to the Healthcare. Using the internet of things in the
Healthcare can automate the workflow of patient care services with help of the Healthcare
mobility solutions as well as other Technologies along with fifth gen wireless networks. Internet
of things allows interoperability, data movement, information exchange and machine to machine
communication which makes Healthcare the most effective (Brady, Carchedi, Polay &
McCAWLEY, 2018). The basic connectivity protocols present in using smart Technologies
within Healthcare special internet of things include Bluetooth LE, Z-wave, and ZigBee, WI-Fi as
well as other advanced protocols.Access to the cloud computation networks helps in storing and

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managing the vast amount of Healthcare data and analyse them properly in a very short time.
The alarm system as the internet of things and wireless network in the Healthcare centres is quite
critical in different events of the life-threatening situations. Medical internet of things devices
shall accumulate vital data as well as transfer these data to the doctors for real-time tracking
(Roberts, Benjamin & Bartek, 2019).
RFID in healthcare
RFID has been introduced in Healthcare as the alternative approach to the sensor based wearable
appliances as well as for presenting the anti-collision system required for the blind people.This is
done by analysing the reflected backscatter signals belonging to the passive tags of RFID which
are closely attached to the clothes of patients. They immediately raise the alarm whenever they
tend to deviate from their normal path and closely approach the obstructions. Numerous
empirical studies have been conducted which identify that the phases together with the RSSI
(Received signal strength indicator) fingerprints can definitely act as the indicators of distance
covered between the Antennas and RFID tags. Recently the wireless sensor Technologies have
highly attracted the interest of intensive research (Xiao, Miao, Xie, Sun & Wang, 2018). They
are mostly based on RFID or Wi-Fi due to the advantages of pervasiveness and non-
intrusiveness.Wi-Fi operates comparatively in a shorter range yet it is extremely position
dependent that is is quite a limitation for Wi-Fi. On the other hand, RFID is the promising
alternative smart Technology for the wireless sensing that includes object tracking access control
activity monitoring and others.
RFID system operates typically on the frequency band that lies between 902 megahertz as well
as 928 megahertz by using the radio link of backscatter. Antonym of RFID communicates with
the passive tags under full duplex mode. RSSI seems to be the measurement of power for

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received signals of radio. In the systems of RFID RSS refers to output which reflects power of
the received signal that is backscattered (Su & Kouritzin, 2018). Longer the distance of
transmission of these signals weaker is the RSS as per the model of path laws that enables the
RSS as a nature to reflect the distance between antenna and tag.
Challenges and issues
Three basic challenges of RSSI can be recognised as:
 RSSI encounters sincere multipath fading class temporal dynamics that causes fluctuation
of the RSSI fingerprints (Kumar, Singh & Gupta, 2019).
 Secondly, the damaged faces that have been measured from the commercial devices of
RFID cannot be used directly that can increase the position of ambiguity.
 On the third antonyms of RFID do not seem to be omnidirectional however can sense
Limited areas of fan at the front of them. Beyond this backscatter signals held by RFID
tags are extremely weak for ensuring the system accuracy (Qian, Zhang, Cao & Zhang,
2018).
 For carrying the RFID tag moving close to the antenna is essential. But in case of
increasing or decreasing the distance between the antenna and tag can create the
problematic condition.
 The multipath effect of the RFID is problematic as part of the managing of indoor
activities.
 The RF phase is associated with maintaining frequency and altitude. The service signal
can be sent by using the offset degree. The measurement is wrapped using a protocol
function. The ranging has to be proper from 0 to 2pie. The tag location cannot be
identified in this stage (Fazal, Shehzad, Tasneem, Dawood & Ahmed, 2017).

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 Measuring the RSSI value is an important part of the anti-collision system development.
Because what are the main challenge of RSSI is its stability. For determining the value
distance, transmission path, transmission power need to be measured include complexity
in terms of developing alarm creation in the indoor facilities.
Solutions to the issues
 For overcoming the challenges of RSSI, measuring the value of RSSI is important. For
the purpose of solving temporal dynamics and multipath fading, the use of LWLR can be
possible. The LWLR is known as a machine learning algorithm which includes the
prediction of data value (Li, Da Xu, & Zhao, 2015). Predicting the data value adjacent
data series is included by regression. For developing a strong RSSI system the use of
fingerprint system design can be possible.
 For the problem of unwrapping the phase is important for each profile for detecting the
continuous value. The distance between the antenna and the tag can be measured in this
process which helps in developing a monitor system for anti-collision (Salim, Setti &
Elabderrahm, 2017). The unwrapping process also eliminates the abrupt challenge of
different phases. Initially, the phase value is wrapped but after unwrapping the position
can be calculated from a different location. For the anti-collision detection, the use of
phase values are not required but for the purpose of guiding the walking path of the
Technology, user can be easily utilised with the help of rate unwrapped phase change. Is
the guidance system can easily be included as a supplement of the anti-collision system in
the process of preventing the walking of the user. This working is been prevented from
the different slanting direction in the way of entering the obstacle monitoring area.
Introduction of the anti-collision system

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In order to realise the application of the system for the visually impaired patients, IAAS (Indoor
anti-collision alarm system) requires identification of distance from a person to the obstacle he or
she faces and instantly provides allowance at the time of approaching these obstacles to a
particular extent (Qian, Zhang, Cao & Zhang, 2018). This works by setting an antenna quite near
to the obstacle as well as attach a specific tag on the clothes of people then the RSSI values are
computed for identifying the distance.In the part of the training, RSS values are collected
whenever the person tense to stand and distinct distances away from the obstacles. The whole
measuring area is then divided into warning zone danger zone and safety zone as per the distance
to obstacles is computed (Goetz, 2018). RSSI officials are needed to be determined for
identifying which area is currently held by the person. In the section of monetary RSSI values
are collected in the real-time and then the fingerprints are extracted together with locally
weighted linear regression (LWLR).Performance of the anti-collision system depends on the
following metrics:
Negative alarm rate: this is the count of different cases where receiver Mrs to send alarms
whenever usual enters that warning zone and even danger zone.
False alarm rate: this depicts the number of distinct cases where the receiver provides the wrong
alarm even if the user tends to be in his/her safety zone (Roberts, Benjamin & Bartek, 2019).
Overall performance of the anti-collision system: for the process of analysing the overall
performance of the anti-collision system, a normal walk needs to start where no danger or
warning zones are available. Besides that, working with warning zone and working including
danger zone is also part of this performance testing process. Therefore three different
backgrounds are being developed which include safe zone warning zone and the danger zone.
For the analysis purpose, these 3 different tracks needed to be separated. In this scenario, an

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individual or user has to start working which helps in analysing which of the zone, he chooses to
enter. The feasibility of the system can be analysed by using this analysis process. Promising
performance can be achieved in the process of avoiding abstract by using this system. After more
than 50 random intervals the system has worked properly (Xiao, Miao, Xie, Sun & Wang, 2018).
Among which to negative alarms and one false alarm is also part of the experimental research.
Most of these errors occurred due to the fluctuation of RFID signals.
Response time of system: the response type of anti-collision system is very important because
high speed is required for involving it in any industry including the Healthcare system. The time
cost management is another part which is related to the rate of RFID device. The complexity of
LWLR can reduce the server response time of the system. Keeping this in mind focuses on given
on the process of eliminating or reducing the time delay for providing real-time performance by

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using the anti-collision system. Finally, the sampling frequency and tag range are part of
computer processing. The data access help in guaranteeing real-time performance by using this
anti-collision system (Su & Kouritzin, 2018). The processing speed improvement can be possible
with LWLR where the training data are being used for predicting the appropriate time. For
instance, it can be said that the result has been gained from the data size. If the data size is large
then the time of learning frequency will be very low. For the purpose of solving this problem, the
concept of the time window in the process of performing LWLR operation needed to be included
for the subsequent shell connection development to complete the data fingerprint. With this
advancement the real-time working of this anti-collision system was ready (Kumar, Singh &
Gupta, 2019).
Management concepts
1. SWOT ANALYSIS
It is important for each and every Healthcare industry to have quality management for improving
the management process. (Rosenbaum, et al. 2016) This will help to improve in the medical
professional prominent position to contribute Hospital quality especially for the people who are
vulnerable. The application of smart technology and anti-collision alarm system have to Improve
the intercommunication between the areas and focused on more transparency for saving
environment for the patient as well as for the workers which include nurses, doctors, staffs, etc.
A SWOT analysis can be applied to understand the defined strength, weakness, of opportunities
and threats of an anti-collision alarm system. SWOT analysis is an intended strategic planning