M. A. Sarijari
Universiti Teknologi Malaysia

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Machine learning based lightweight interference mitigation scheme for wireless sensor network Ali Suzain; Rozeha A. Rashid; M. A. Sarijari; A. Shahidan Abdullah; Omar A. Aziz
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14879

Abstract

The interference issue is most vibrant on low-powered networks like wireless sensor network (WSN). In some cases, the heavy interference on WSN from different technologies and devices result in life threatening situations. In this paper, a machine learning (ML) based lightweight interference mitigation scheme for WSN is proposed. The scheme detects and identifies heterogeneous interference like Wifi, bluetooth and microwave oven using a lightweight feature extraction method and ML lightweight decision tree. It also provides WSN an adaptive interference mitigation solution by helping to choose packet scheduling, Acknowledgement (ACK)-retransmission or channel switching as the best countermeasure. The scheme is simulated with test data to evaluate the accuracy performance and the memory consumption. Evaluation of the proposed scheme’s memory profile shows a 14% memory saving compared to a fast fourier transform (FFT) based periodicity estimation technique and 3% less memory compared to logistic regression-based ML model, hence proving the scheme is lightweight. The validation test shows the scheme has a high accuracy at 95.24%. It shows a precision of 100% in detecting WiFi and microwave oven interference while a 90% precision in detecting bluetooth interference.
Development of android-based apps for courier service management A. Mohd; R. A. Rashid; A. H. F. Abdul Hamid; M. A. Sarijari; M. R. A. Rahim; H. Sayuti; M. R. Abdul Rashid
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 2: August 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i2.pp1027-1036

Abstract

E-commerce has grown exponentially over the years. The growth has been characterized by strong consumer demands and the increasing number of various products available online. This in turn creates a logistical problem and a high demand for an efficient courier service to support the growing markets. It is very important for courier service provider that the delivery of the parcel is being done as fast as possible. One of the courier service’s vital and most crucial business process is in the last mile parcel delivery. This is where an efficient delivery service will be of utmost importance. An efficient system needs to be developed in order to facilitate the interaction between the courier service provider and consumer to precisely determine the optimal route for the parcel delivery. In this paper, an Android-based application system for courier service management with last mile route tracking module is developed. It is a mobile application that eases the courier delivery personnel in finding their way to deliver the parcels to the customer’s doorstep. The application will guide the courier personnel to get a list of courier data such as address and contact information and then navigate them to the selected customers’ addresses based on traffic data retrieved from Google Maps API. It will choose the best route to the address and notify the customers before arriving so that the customers are ready to receive the parcel. This last mile route tracking for parcel delivery will provide the basis for an efficient courier service system.