No abstract

Recent discovered technologies have exposed many new theories and possibilities to improve our standard of living. Medical assistance has been a major research topic in the past, many efforts were put in to simplify the process of following treatment prescriptions. This paper summarizes the work done in developing LoRa driven medical adherence system in order to improve medicine adherence for elderlies. The designed system is composed of two sections; embedded hardware device for the use of patients at home and Web application to manage all patients along with their medicines and keep track of their medicine intake history. LoRa wireless communication technology is used for connecting all embedded devices with a central gateway that manages the network. Hardware and software tests have been conducted and showed great performance in terms of LoRa network range and latency. In short, the proposed system shows promising method of improving medicine adherence.

Glaucoma is one of the second driving eye sicknesses on the planet, if not treated appropriately may cause perpetual visual deficiency. Glaucoma is one the irreversible process. There are no particular evidence for this infection, it is seen by loss of side vision. Glaucoma is a moderate dynamic degeneration of retinal ganglion cells (RGC) and their axons, bringing about a particular appearance to the optic nerve head (ONH), regularly called measuring. Because of measuring, the glass zone increments and causes loss of side vision. Typically uncommonly prepared clinicians physically review the funds pictures in a tedious way. In this unique circumstance, we are attempting to build up some novel calculations for programmed discovery of eyes influenced with glaucoma utilizing picture preparing separating and change procedures and actualize the same on equipment utilizing DSP Texas Instruments (TI) DM3730 construct framework in light of chip (SOC) minimal effort, low power single board PC framework or utilizing LABVIEW based NI interfacing framework. The product that will be created by us could be inserted on the equipment to test the solid and unfortunate funds pictures for the recognition of glaucoma. Programmed glaucoma screening utilizing a TMS320C6416DSK DSP board is the equipment that could be considered for usage purposes. The calculations that could be created can be executed on retinal pictures in VERILOG HDL utilizing Xilinx ISE, MATLAB and MODELSIM. TI based pack or NI based unit (any one) is the equipment device that is considered for execution purposes.

The number of older people is increasing in many countries. By 2030, it is estimated that 15% of the overall population will be comprised of people aged 65 and above. Hence, the monitoring and tracking of elder activities to ensure they live an active life has become a major research topic in recent years. In this work, an elderly sub-activity tracking system is developed to detect the sub-activity of the elderly based on their physical activities and indoor location. The physical activities tracking system and indoor location system is combined in this project to enhance the context of the elderly activities (i.e. sub-activities as defined in this project). An indoor location system is developed by using Bluetooth Low Energy (BLE) beacon and BLE scanners to measure the Received Signal Strength Indicator (RSSI) signal to detect the location of the elderly. The activity tracking is carried out via a waist wearable device worn by the elderly. Random forest and Support Vector Machine (SVM) are used as machine learning classifiers to predict the activity and indoor location with an accuracy of 95.03% and 86.58%, respectively. The data from activity tracking and indoor location sub-systems will then be combined to derive the sub-activity and push to an online Internet of Things (IoT) platform for remote monitoring and notification.

<span>An Internet of Things (IoT) FPGA-based home hub to automate control operations in a home environment was designed and built. The proposed system uses an FPGA home hub as its local analytic engine with an IoT platform to store the sensory data. The FPGA was programmed in Verilog HDL using Quartus II provided by Altera. The WiFi capability of the FPGA was extended through an ESP8266 chip to ease the interfacing with various sensors connected to it. The system can be configured and monitored through a web application coded in JavaScript. Various test cases were carried out on the implemented system at Multimedia University (MMU) Digital Home Lab. The results verified the functionality of the system in triggering real home appliances (i.e. air conditioning unit and lighting) based on multiple sensor nodes without conflicting each other. The ability to allow user to configure the control rules based on the sensory data via web interface hosted using ThingSpeak Plugins is also presented and demonstrated in this project. The base design is utilizing Altera Cyclone IV EP4CE22F17C6N FPGA with 153 I/O pins, which is highly scalable and adaptable to the requirements of home environments. This shows promising application of FPGA in supporting scalable IoT home automation system.</span>