Wireless Sensor Development for Malaysian Forest Monitoring and Tracking System

Ghazali, Muhammad Azim; Othman, Kama Azura; Isa, Mohd Ashraf Hakimie Mohd; Baharuddin, Mohd Asyraf

doi:10.1109/icsec.2017.8443938

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…A recent study was done in 2017 on the development of a wireless sensor for Malaysian forest monitoring and tracking system [3]. This study focused about wildlife extinction and creating a certain measure of control to prevent extinction of the organism in the forests.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of Monitoring System using the Internet of Things for Industrial Revolution 4.0

Jaafar¹,

Abdullah²

2020

IJITEE

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The fourth industrial revolution represents smarter systems, faster and more optimized system of artificial intelligence, which involves control systems and sensors networks. In this paper, the concept of the Internet of Things (IoT) was applied preliminarily to create the connection between machine and the user, using a sensor, a processor such as Raspberry Pi, and IoT platform application such as Blynk in the smartphone. The simple IR 4.0 prototype system and IoT apps were developed in order to create a connection between sensors and user through the internet consisting of a temperature and humidity sensor, which is DHT11 and a Raspberry Pi 3 Model B. The smartphone application would be developed through the Blynk application for this simple prototype system. The graphical user interface GUI was built within the Blynk app and link it to the sensor which is already connected to the Raspberry Pi. The analysis that was done upon the system is by varying the stimuli to the sensors, which is a hairdryer with three levels of heat and observe the relative change of the reading of temperature and percentage of humidity on the apps. Therefore, the preliminary result shows an increase in temperature as the heat level increases. On the other hand, the percentage of humidity becomes lower as the temperature goes higher. Based on the results and the analysis, it had shown that the IR 4.0 prototype system of IoT monitoring can connect between the sensor and the smartphone application with real-time monitoring through the internet.

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Section: Literature Reviewmentioning

confidence: 99%

Development of Monitoring System using the Internet of Things for Industrial Revolution 4.0

Jaafar¹,

Abdullah²

2020

IJITEE

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“…Other devices rely on wireless technology that is power inefficient, and battery degradation happens withing hours and the harvested energy is consumed quickly. For example, in Ghazali's et al [2] tracking system the battery voltage dropped by more than 20% within an hour. Additionally, several of these technologies and applications lack a network with data collection capability between wireless nodes.…”

Section: Introductionmentioning

confidence: 99%

Building an Energy-Efficient Ad-Hoc Network for Wildlife Observation

Camal

Akşanlı

2020

Electronics

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This study evaluated the design of an energy-efficient ad-hoc network used for wildlife observations, particularly in order to understand the social relationships in an animal group, where the distance between individuals, i.e., proximity, can be used to measure a relationship. Our proposed network consists of a full mesh topology and contains nodes that communicate via Bluetooth Low Energy (BLE) in advertisement mode. The initial hardware configuration and software algorithm duty cycles the BLE communication to on and off states using a parameter called the BLE active triggering interval. The algorithm is improved by placing the BLE subsystem and CPU in deep sleep when there are no BLE or CPU tasks to process. This improves the power performance by up to 94.48%. To scale up power optimization and track the trade-off between power and throughput, we created a simulator that modeled our network with dynamic wireless sensor nodes. The simulator verified the base case hardware results. It also showed a median power performance increase of 97.79% in comparison to the base case, yet throughput decreased by 66.65%. The highest power performance increased by 98.89% when a wireless sensor node was configured with a BLE active triggering interval of 50 s and its CPU was set to 14 MHz; however, the simulator showed a throughput drop of 79.97%. Depending on the application, a design may tolerate the decline in throughput to achieve higher power performance.

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Wireless Sensor Development for Malaysian Forest Monitoring and Tracking System

Cited by 2 publications

References 8 publications

Development of Monitoring System using the Internet of Things for Industrial Revolution 4.0

Development of Monitoring System using the Internet of Things for Industrial Revolution 4.0

Building an Energy-Efficient Ad-Hoc Network for Wildlife Observation

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