I am writing a project proposal for seed funding for an engineering project. The project proposal should include the part Project Summary, Introduction, Goal and Objectives, Current Situation, Product Overview, Technical Description, Benefits, Project Team, Schedule, Budget, Conclusion and References. This proposal should be written for non-expert target funders. Specifically, I am writing the Benefits part. My project is named “Waveguard”, and my project outline is :
“
OBJECTIVES
Users will be able to
- monitor the motions and different vital signs of them/ their elderly family who live alone remotely through the real-time millimeter wave (mmWave) based system and artificial intelligence (AI) algorithms
- gain timely medical support by notifying the medical personnel/their family through the wireless communication speaker system
PROBLEMS/NEEDS/OPPORTUNITIES
- Aging Population: Demographics shift towards more elderly individuals, over 1 million of the population are aged 65 or above in Hong Kong.
- Safety Concerns: The Unintentional Injury Survey 2018 conducted by the Department of Health (DH) showed that fall was the most common type of unintentional injury, accounting for 39.4% of all injury episodes that occurred over a 12-month period. Falls and accidents pose serious risks to the solitary elderly as they may not be discovered very soon, necessitating early detection and intervention.
- Healthcare Challenges: About 70% of the elderly in Hong Kong are suffering from chronic diseases, most commonly diabetes and hypertension. Timely health condition monitoring and treatment are needed, especially for the solitary elderly.
EXISTING SOLUTIONS
- Vision-based detection systems, e.g. video cameras, depth cameras, and thermal cameras: Have privacy issues and low detection accuracy in low light, clothing cover environments.
- Non-vision-based sensors, e.g. acoustic-based systems, vibration-based systems, infrared-based systems and radar-based systems: Limited by the effect caused by environmental noise.
- Wearable devices, e.g., smartwatches and IMU devices: Inconvenient and unacceptable because the elderly may forget to wear the device.
KEY FEATURES AND FUNCTIONS
- A mmWave-based monitoring system that can detect and recognize different motions of the elderly, e.g. standing, walking, sitting on a chair, sleeping on a bed, opening a door, opening a cupboard, picking up the pole stand, drinking water from a bottle, fall, etc and different vital signs, e.g. respiration and heart rate, by leveraging mmWave sensing and machine learning technology.
-In the proposed system, the mmWave FMCW radar transmits the frequency-modulated continuous wave through transmitting antennas in order to impinge on the target, which here is a human. The scattering EM wave is received by receiving antennas and then is transformed into point clouds and doppler velocity. The point clouds and doppler velocity are selected and grouped as an input dataset of the intelligent system using the LSTM network for fall detection. Before feeding the input data, including point clouds and doppler velocity, into the LSTM network, data preprocessing, including data filtering, data averaging, and sliding window processing, was performed. In the data preprocessing, the point clouds at zero doppler velocity, often called spurious data, are filtered out. The filtered point clouds scattered from many targets and received by many receiving antennas are averaged to attain point clouds in a direction in one dimension. The filtered and averaged point clouds in the zaxis direction, and doppler velocity, are fed into the LSTM network, which is employed to intelligently detect the fall of an elderly person. The data preprocessing and detection were done using a processor. The processor of the radar will send a notification to the computer server through communication networks such as 4G, 5G or Internet networks if a fall is detected. The server receives the notification and then does a few processing steps such as counting the number of detected falls, storing data in data lockers, and matching the elderly individual that is monitored by the radar to one or more elderly caregivers. The server will send a push notification to the caregiver’s mobile application in order to warn a caregiver about all. A notification will be resent only when the caregiver takes care of the fall and pushes the button ‘‘took care’’ on the mobile application and then a new fall is detected.
- Combined with a wireless communication-based system and speaker that directly contacts and communicates with the medical personnel and the elderly’s family when detecting accident or emergency situations.
- Using IWRL6432 as mmwave sensor:The IWRL6432 is a mmWave radar sensor developed by Texas Instruments that focuses on high-performance while consuming low power. This radar sensor opens up new possibilities for industrial applications, as it can be used in low-power and battery-powered devices.
- A program (software application) for the hospital and elderly’s family to monitor the elderly’s health situation consistently in real time.
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A good Benefits part should be:
-persuasive and parallel headings highlighting the specific benefits
-explores the impact/benefits from different angles
-avoid passive verbs, static verbs that lack movement (e.g. have, do, could, should, would) and vague verbs (e.g. get, go, put)
-use positive action verbs
-concise


My ntroduction, Goal and Objectives and Technical Description part :
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Introduction
The ageing demographic in Hong Kong poses unique challenges as the number of individuals over 65 has surpassed 1.45 million in 2021 [1]. This shift raises safety concerns, particularly the risk of falls, which, as reported by the Department of Health’s Unintentional Injury Survey 2018, represent a significant 39.4% of unintentional injuries among the elderly [2]. Often living alone, these individuals are vulnerable to accidents that can remain unnoticed for extended periods, emphasizing the need for prompt detection. Furthermore, roughly 70% of this elderly cohort battles chronic diseases like diabetes and hypertension [3], necessitating constant health monitoring.

Given these facts, the consequences are severe: increased duration of hospital stays, a decline in quality of life, and greater economic pressure on families and the healthcare system. Therefore, timely intervention is critical in elderly care to maintain our commitment to both compassion and life preservation. Waveguard detects motions and vital signs such as respiration and heart rate without compromising privacy or accuracy. Coupled with a communication system to alert medical personnel or family members in emergencies, Waveguard seeks to reduce the time it takes for solitary elderly individuals to receive medical attention after an incident, therefore mitigating the severity of injuries from falls and expediting the response to critical health events.

Goal and Objectives

Goal
To improve the quality of life and physical health of elderly individuals living alone by providing assistance in dealing with daily risks through the support of “Waveguard,” an advanced detection system designed for safety and protection.

Objectives
Users will be able to
•	monitor the motions and different vital signs of them/ their elderly family who live alone remotely through the real-time millimeter wave (mmWave) based system and artificial intelligence (AI) algorithms
•	gain timely medical support by notifying the medical personnel/their family through the wireless communication speaker system


Technical Description

Millimeter Wave Sensing Technology
Waveguard utilizes state-of-the-art millimeter-wave (mmWave) sensing to monitor the well-being of the elderly, particularly in scenarios where they are living alone. The mmWave Frequency-Modulated Continuous-Wave (FMCW) radar functions by emitting a high-frequency wave that is capable of detecting minute movements [4]. Upon hitting a target, such as a person, the wave is scattered back to the system’s receiving antennas, capturing critical data which is then transformed into point clouds and Doppler velocity information. This wave efficiently works through clothing and does not require direct line-of-sight, making it invariant to light conditions and visual obstructions typical in a home setting without compromising privacy, as it does not produce visual images of the subjects it monitors.

AI-Driven Fall Detection
Central to the ‘Waveguard’ system is its AI and machine learning core, which uses Long Short-Term Memory (LSTM) networks [5]. These are a type of recurrent neural network (RNN) well-suited for sequence prediction problems and are used to interpret the captured mmWave data. This sophisticated AI framework has been trained to reliably differentiate between regular activities such as walking, sitting, or lying down and critical events like falls. Real-time interpretation of these activities is reinforced through continuous monitoring of vital signs, including respiration and heart rate, offering a comprehensive health assessment of elderly individuals.

Real-time Communication and Notification System
Once the onboard processor within the mmWave device detects a fall, it transmits a signal to a dedicated server via existing communication networks like 4G, 5G, or Wi-Fi. The Waveguard server performs several processes, such as logging the incident, identifying the affected individual, and coordinating notification dissemination. Caregivers or family members then receive an alert through a specially designed mobile application. Furthermore, in critical conditions where emergency services are needed, Waveguard includes a wireless communication-linked speaker system, facilitating direct contact with medical personnel or relatives. This ensures not only timely medical intervention but also constant reassurance for the elderly and their families that help is always at hand.

Mobile Application
The Waveguard system is complemented by an intuitive mobile application that serves as the interface between the monitoring technology and the caregiver or family member. Users receive push notifications about falls or vital sign anomalies through this app and can acknowledge incidents by indicating that they have ‘taken care’ of the situation. The app features a user-friendly dashboard that enables family members or caregivers to monitor vitals and motion in real time, maintain logs of incidents, and receive alerts.

Energy Considerations
To ensure that Waveguard remains an effective tool for continuous monitoring, it will be meticulously engineered to maximize energy efficiency. The IWRL6432 mmWave sensor embodies the essence of energy efficiency with its sophisticated low-power 45nm RFCMOS process engineered to deliver high performance while minimizing power consumption [6], thereby ensuring prolonged operational periods without compromising system responsiveness. Furthermore, potential future developments may introduce energy-harvesting capabilities, such as capturing energy from ambient light or heat differentials, to extend battery life. These measures will ensure that Waveguard can provide 24/7 monitoring without the need for frequent maintenance or disruptions—key to the system’s reliable use in real-world scenarios.

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Write the Benefits part for about 200 words. You can add your own knowledge; if there is extra information needed, please let me know.