This project presents the design of pocket-sized halal sensor used to detect lard adulteration in oil using dielectric spectroscopy method. This system will feature the application of Interdigitated Electrode (IDE) connected to Analog Devices’ AD5933 Evaluation Board to measure impedance and a mobile app that acts as the User Interface.

The whole system will be connected using Arduino, specifically Arduino Uno and an HC-06 Bluetooth module. The main motivation of the design is to provide a portable, real-time and accurate lard measurement device which is quite scarce in the market.

Besides that, this project will also focus on the performance of dielectric spectroscopy in detecting lard adulteration. Lard adulteration will be measured using the system designed and the sensor’s performance is measured via FAVORIOT IoT Platform.

Physically, the system consists of the following components:

Figure 1: System components

Figure 2: Mobile app connected to the sensor using Bluetooth. [1] Select device page. [2] Homepage when no device is connected. [3] Homepage when the device is connected.

[Note: This project is being developed by UPM, our FAVORIOT’s University’s collaborator. Article was written by Nurhani Amirah Adenan]

It’s no doubt that the whole world is facing an Ageing population. In 2017, there are an estimated 962 M people aged 60 or over in the world, comprising 13 % of the global population. The population aged 60 or above is growing at a rate of about 3 % per year. With the progression in healthcare, people tend to live longer than before, however, not necessarily healthier. They might suffer several chronic diseases such as Diabetes, high blood pressure or Dementia.

It was stated 500K elderly people gone missing in China every year or 1300 elderly people went missing every day due to loss of memory. Senior citizens aged 65 or over account for up to 80% of missing elderly person cases (Alzheimer or dementia or memory impairment). Of those who were found after being reported missing, 25% then went missing again.

Statistics have shown that approximately 30% of people over 65 falls accidentally each year, and for those over 80 this rate raises up to 50%. Late or non-existing responses cause 2 million persons having to be hospitalized and approximately 85K deaths can be attributed each year. Among older persons, 55 % of fall injuries occur inside the home. An additional 23 % occur outside, but near their homes.

Thus, there are three key things that we consider very seriously for the elderly well-being (i) continuous monitoring of their vital health conditions (ii) monitoring their location in case they get lost (iii) emergency alerts during falls.

The trend is moving towards “Aging in Place” whereby we are seeing the elderly are staying alone especially in countries where they have less number of children or the culture whereby the children or the parents prefer to stay on their own. As a working adult, they have no options but to let their parents stayed at home by themselves. In such case, it will bring high anxiety especially when their parents suffer some disease or in a frail condition.

How do we let the elderly to “Live Alone but Not Left Alone”? What if we have a way to monitor their health continuously? What if we know they are always active or just lie on the bed? What if we get notified whenever they walked outside their house? What if they need emergency and need to call their next of kin or neighbor easily? What if you constantly call them directly without them carrying a mobile phone?

All of the above is possible using our Favorwatch. Check out the details here.

Anyone willing to join the mission to connect and help 1 Million elderly around the world?

Abstract

The Smart Bracelet for Elderly People is an innovative solution that aims to detect and locate people especially for elderly people with a health problem. It is designed as a remote alert system for people at risk of stroke, sudden heart attack, and seizures. The smart bracelet provides fall detection system, GPS tracker to trace the current location and a medicine reminder setting to remind pill intake on time. This device is synchronized with the FAVORIOT platform which stores GPS data and fall detection indicator.

Result

This section shows the preliminary result from the prototype testing for fall detection, GPS tracker and Medicine Reminder coding.

[Note: This project is being done by UTHM, our FAVORIOT’s University’s collaborator. Article was written by Siti Nur Hanisah Binti Hamidon, Siti Khadijah Binti Narudin, Siti Norliani Binti Ahmad Basni Supervisor: Dr. Ansar Bin Jamil, FKEE UTHM]

You can check out the whole LIST of IOT PROJECTS by our University Collaborators.