Monthly Archives: February, 2018

Pocket-Size Halal Sensor Based on Dielectric Spectroscopy

February 19th, 2018 Posted by HOW-TO, Internet of Things, IOT PLATFORM, SMART HEALTH 0 thoughts on “Pocket-Size Halal Sensor Based on Dielectric Spectroscopy”

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]

Remote Optical Sensor for Ammonia Detection in Water

February 17th, 2018 Posted by HOW-TO, IOT PLATFORM, SMARTCITY 0 thoughts on “Remote Optical Sensor for Ammonia Detection in Water”

Ammonia is a chemical compound that made up of two gases which is nitrogen and hydrogen. Ammonia can be found in several advantages and disadvantages toward human and environment. The advantages of ammonia can be seen from it is very useful that can be used in many industries such as in agriculture, food processing, petroleum, rubber, and other industries. For example, we can see that from agriculture, it is used for livestock feeds, fertilizer, and crop protection. In petroleum, it is used for the protection of equipment to avoid corrosion.

However, during the manufacturing process from industry, there will produce wastewater that contains a concentration of ammonia. When ammonia reacts to water, there are two chemical species exist in water which is in un-ionized form, NH3 and ionized form, NH4. The unionized form is called ammonia whereas ionized form is called ammonium. These two forms which together are called total ammonia nitrogen or in short forms TAN. At the same time, the weak base is formed which means the pH value is greater than 7. It is very important to know that the unionized form is toxic. Therefore, this toxicity will bring negative effect to the environment and may harm aquatic life.

In this project, remote optical sensor towards ammoniacal nitrogen in water will be developed to give an alert if ammoniacal nitrogen is detected in water. For the cloud including the server, database, and the interconnection between it, FAVORIOT IoT platform will be used.

[Note: This project is being developed by UPM, our FAVORIOT’s University’s collaborator. Article was written by Ng Foo Guan]

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

Robust Vision-Based Human Detection in a Dynamically Varying Environment

February 16th, 2018 Posted by HOW-TO, IOT PLATFORM, SMARTCITY 0 thoughts on “Robust Vision-Based Human Detection in a Dynamically Varying Environment”

Regardless of various research endeavors, the performance of current human detection system is still a long way from what could be utilized dependably under varying realistic environment. This is expected to some extent to the inborn troubles related to the human body and nature in which it is found. The non-unbending nature of the human body offers to ascend to varieties in the stances that it can accept and when this is combined with movement a few displaying issues are exhibited. Because of some position and angle of the camera, the view and size varieties represent some technical difficulties to the models that can be implemented. It is different with other objects that normally show up in one shape, people can be dressed in any form of changing shading and surface. The location of the human object in the environment is an essential part of the appearance. For example, the environment illumination could upgrade or corrupt the appearance relying on the direction and nature of the light. Most of the challenges with complex background are mostly experienced in the open area. Occlusion is always a challenge for robustness with several human and interactivities. This might be the parts of body cover with another part of a body which create inter-object occlusion which happens when one human walk in front and another human is behind.

As a result, we propose to develop the vision-based human detection system with Artificial Intelligence method: Deep Neural Network and Internet-of-Things (IoT) technology to strengthen the robustness of the system. FAVORIOT IoT Cloud platformact as a middleware will be fully utilized to store images to prevent data loss through the internet.

[Note: This project is being done by UPM, our FAVORIOT’s University’s collaborator]

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

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