Health
FPGA based Body Area Anomaly Detection System Design for Healthcare
AS036 »
Currently, wireless communication network applications are becoming part of our daily life that cannot be ignored. One of the most important is healthcare application. Physiological and health condition of a person can be detected, processed, transported, and stored easily in (wireless) body area network (W)(BAN). WBANs have several applications including in sports, interactive gaming, military, and security. For instance, aged people show larger dependence on the healthcare system because of age related diseases like cardiac ailments, respiratory problems, arthritis, neurological diseases, and dementia. According to World Health Organization (WHO), by 2047 people 60 and above will be 2 billion, up from 841 million in 2008. According to the US Bureau of the Census, in US alone elderly people are expected to 70 million by 2025, the healthcare expenditure is about $5.4 trillion, which will represent 20% of the GDP. Hence, smart and interactive wireless healthcare system can leverage both the health and economic issues of users.
The three-tier communication architecture of WBAN consists of, (i) BAN node: each node is integrated with biosensors (ECG, SpO2, temperature, etc.) to record patient’s dynamic body parameters and movements; (ii) LPU (Local Processing Unit): to gather data from BSNs and provide to the physicians. It also a router between BAN nodes and the central server using Bluetooth and Wi-Fi for short range and mobile networks for long-range transmission. (iii) back-end infrastructure: which consists of (a) CS (Central Sever), which feeds the patient data to the PD (Patient Database) and (b) Physician Workstation.
The challenges in WBAN are, reliable data transmission, node mobility support and fast event detection, timely delivery of data, power management, and security. Medical data networks are increasingly exposed to external attacks. Safety and privacy of medical data must be guaranteed all the way from the sensor nodes to the back-end services. On the other hand, energy efficiency issue exists at different sensor nodes, and communication and data processing subsystems.
This work focuses on developing a new FPGA based body area anomaly detection system using machine learning techniques by training the behavioral change of body area environment (i.e., indoor and outdoor). Because FPGA is an integrated circuit that contains a large resource of logic gates and memory, it is possible to implement parallel digital computation and executions. This leads to low latency and minimum energy consumption. Hence, we propose system on Chip (SoC) (i.e., Microcontroller Unit (MCU), Central Processing Unit (CPU), and FPGA) at both ends of WBAN system. It enables a wide range of healthcare applications such as ubiquitous health monitoring (UHM), computer assisted rehabilitation, emergency medical response system (EMRS), and promoting healthy living styles.
The objective of this work is to design an energy efficient and secure WBAN for pervasive healthcare system, which reduce patients visit to hospitals. Specifically, to transmit and store medical data securely keeping the privacy, authenticity, availability, and integrity of medical data at the three layers of the WBAN architecture, and to model a power efficient WBAN during data processing and transmission.
Water Related
Water Quality Analyzer
AP086 »
Water is a vital factor in human life and for the existence of other habitats. Easy access to safe water for drinking, domestic use, food and production is a civic health requirement. Therefore, maintaining a water quality balance is very essential for us. Otherwise, it causes serious health problems to humans. Water contamination has been studied as one of the leading causes of death and illness in the world. Many people die from contaminated water every year. One reason is that public and government ignorance and the absence of water quality checking systems cause severe medical issues.Water contamination is also a serious issue in industries, irrigation and aquaculture.
Traditionally, water quality detection is done manually when water samples are taken and sent to the laboratory, but this process requires a lot of time, cost, and human resources. These techniques do not provide real-time data. By considering these challenges, we have come up with an idea to design a Water quality analyzer to check the quality of the water used for different purposes.
The Process starts from taking the real time data from the water bodies using sensors and type of water need to be checked must be selected from the mobile app. FPGA Board processes the collected data and compares it with the standard data in order to assess the water quality.The quality parameters of the water and the quality of the water will be sent to the mobile app using IoT Technology. If the quality of the water is below the desired levels, an alert will be sent to the user. In this way we can have continuous real time water monitoring.
Autonomous Vehicles
Autonomous Disinfection Robot
AP087 »
In recent years, international socioeconomic development and medical reforms have permitted the medical industry to move toward true "intelligence". The outstanding developments in medical technology have helped people overcome many challenges in life. Especially, during the global pandemic of COVID-19, besides the development of vaccines, the application of advanced technical technologies also helps people slow down the increase of the disease. The incorporation of greater artificial intelligence, internet of things in to develop robots that automatically disinfect the air and surfaces of hospital environments can help reduce the human resources spent on environmental cleaning and disinfection and minimize the risk of occupational exposure for staff. These robots also facilitate informatized management of environmental disinfection, reduce costs, and increase the efficiency of disinfection efforts.
In this study, we propose to deploy a type of autonomous disinfection robot with the ability to automate tasks such as: Automatic scene recognition and disinfection; Automatic movement and avoids obstacles; Collect patient's body temperature and blood oxygen to assist in building a chart to monitor the patient's health automatically.
The autonomous disinfection robot applies AI algorithms and robotic technology to the field of hospital disinfection. In essence, the model is a disinfection robot with a high level of independent self-sensing AI. The robot model uses intelligent scene recognition, independent sensing in the disinfection process, real-time disinfection process monitoring, intelligent planning, independent execution, and evaluation of the results. An intelligent disinfection robot can compensate for the shortcomings of existing disinfection methods, improve the quality of disinfection, and reduce the probability of infection.
Food Related
Herbal plant recognition and monitoring
AP088 »
The project aims to recognize common herbal plant in the Philippine setting, both grown by gardeners and in the wild. Our project also aims to check the viability of the area for growing these herbs by monitoring how many are growing in the area/presence of clustering, plant part status such as checking leaf condition such as drooping and wilting, and presence and absence of invasive plants/animals that can affect the survival of the herb using computer vision. Other parameters such as humidity and sunlight will also be monitored using ADI boards provided. The data collected will be sent to Microsoft Azure platform where partner NGOs and stakeholders can view the data and insights generated to help make sound decisions that will benefit the community they're helping.
Food Related
Mini Biogas Plant with AI Implementation for Parametric Optimization of Biogas Yield
AP089 »
According to the Food and Agriculture Organization (FAO) of the United Nations, one third of the food produced is wasted and the financial costs of food waste in the world could total to USD 1 trillion each year. According to United Nations Environment Programme (UNEP), approximately 1.3 billion tonnes of food is wasted annually. Besides, Asia produces 50% of global food waste with China, Japan and South Korea alone contributed to 28% of the global disposed food. According to the Future Directions International (FDI), South and Southeast Asia on the other hand contributed to 25% of global food waste. In Malaysia, the food waste produced is 2,921,577 tonnes per year from households alone. This is equivalent to 91 kg of food waste per capita per year generated in Malaysia. This is concerning since Malaysia is the highest country to produce the amount of food waste among Southeast Asia countries.
To address the problem of excessive food waste in Malaysia, biogas could be a solution. Biogas is a renewable energy source produced by the breakdown of organic matter such as food waste to produce mainly methane and carbon dioxide gases which are environmentally friendly. Another end product which is the digestate can also be used as fertilizers since it is rich in nutrients. Globally, coal and natural gases are mainly used to generate electricity – even cooking. With the used of biogas to occasionally replace these two resources is seemed to be more sustainable since biogas is renewable energy – more resources could be saved.
In line with the aim of this year's InnovateFPGA competition, which is "Enabling the Edge for a Sustainable Future", a mini biogas plant with AI monitoring features capable of producing methane gas from food waste through Anaerobic Digestion (AD) is proposed under the food waste category to help address the problem of excessive food waste particularly in Malaysia. This mini biogas plant will be smaller compared to the other biogas powerplant in industry which means it is also portable and just can be put in the backyard. All the food waste generated daily in the household could be ‘reused’ for two main purposes: heating (for cooking) and electricity. Several key parameters are affecting the AD process: pH, temperature, C/N ratio, Volatile Fatty Acids etc. The use of FPGA in this project is to provide an Artificial Intelligence (AI) implementation to the system to optimize the biogas yield from the food waste by controlling the pH and the temperature.
Other: Smart city + food related
Smart garden
EM030 »
It is about how we have a good garden , how we have healthy food, and how we do them in smart manner .
Food Related
Sustainable Agriculture
AP091 »
We are going to build a cloud-based remote hydroponic farm environment system that will capture the raw data from the farm, remote plus autonomous control of the farm activities, automated crop growth estimation & analysis. We are already working on this project based on a microcontroller and moving towards the FPGA based implementation due to its several benefits.
Marine Related
Biodiversity
AP092 »
I want to create an IoT based solution for the given SGP project Idea "Mauritius: improving Livelihoods of Communities- Oyster Farming for Jewelry Making in Rodrigues" which will collect all the problem statement mentioned data and share the data as well as specific high swell, theft warning through the azure cloud platform.
Other: IOT
Stolen Vehicle Recovery - Anti Theft Solution
AP093 »
Vehicle theft is becoming a growing problem. Thieves are very organized and can steal a vehicle in seconds as statistics show all over the world. Meanwhile, police fail to recover more than half of stolen vehicles. For criminals, it is a low-risk way of making a fortune,
According to Interpol, the use of the Internet has contributed to a dramatic increase in the resale of illicit automotive components in recent years.
This has become a worry for car owners, insurance providers, and car manufacturers.
Most anti-theft solutions are run by a vehicle's central command, which is easy to override.
Stolen vehicle recovery has become more convenient with IoT technology and GPS sensors.
IoT devices that can be installed in cars have low maintenance costs and are energy-efficient.
The devices that are small and easy to conceal can be fitted in multiple spots in a car.
They can get a stolen vehicle’s location based on the slightest signal, and they also offer a wide area of coverage.
So in our design, we aimed to show the intelligent use of FPGA and Azure IoT in detecting thefts very easily.
Features:
1) GPS tracking
2) Interactive user interface
3) Owner's Face recognition
4) Towing detection
5) Vehicle engine blocker(Blocks engine starter when jammer detected)
6) Manual & autonomous driving modes
Smart City
Smart off sensor
AS037 »
To be able to determine with a higher likelihood when to be be able to turn off electronics, lights, set air conditioning higher and not to interrupt someone at home simultaneously.
Smart City
NDVI device for building building monitoring
EM031 »
We have developed a platform to measure and visualize Normal Difference Vegetation indices using a low cost Camera and a DE2 board. This device was tested on building facades showing building moisture that can be related to the inhabitant health. In a different project we have studied around 17000 buildings in Beirut to build and energy model, the simulation was run on Azure. In this proposal we try to merge the two concepts/techniques.
Other: SGP - Biodiversity
MEDICINAL PLANT PLUCKER
AP094 »
Plants are considered as one of the greatest assets in the field of Indian science of medicine called Ayurveda.Some plants have it's medicinal values apart from serving as the source of food.The innovation in the allopathic medicines has degraded the significance of these therapeutic plants. People fail to have their medication at their doorstep instead went behind the fastest cure unaware of its side effects.
The main reasons are extinction of medicinal plants and lack of knowledge about identifying medicinal plants among the normal one's.Plant from the basis of Ayurveda and today's modern day medicines are great source of income.Due to cutting of forests,lot of medicinal plants have almost become extinct.Because of Ecosystem is the major part of Biodiversity,Where plants plays a crucial role. So we have to replant the extincting medicinal plants to improve our Ecosystem And to do not disturb Biodiversity.
So there is an immediate need for us to identify medicinal plants and replant them for next generations.Medicinal plants identification by manually means often leads to incorrect identification.
This project aims at implementing a System which can be able to identify some medicinal plants and Plucking of plants if they are medicinal.