Posts Tagged ‘WSN’

Teknologi WSN untuk mendeteksi kebakaran hutan

September 17, 2019

Beberapa hari ini, saya melihat dan mendengar dari berbagai sumber media, baik itu media pers maupun sosial media yang memberitakan tentang kebakaran hutan di Indonesia; khususnya di Kalimantan dan Sumatera. Memang sangat disayangkan atas kejadian kebakaran atau “pembakaran” hutan ini. Diperlukan kesadaran akan perlunya menjaga lingkungan hidup, alam sekitar, terutama hutan sebagai jantungnya keberlangsungan ekosistem di dunia yang kita tempati ini. Tapi saya tidak akan membahas apa penyebab dan akibat dari kebakaran hutan tersebut. Ini masalah yang sangat pelik, karena masalah ini sangat beririsan dengan kebijakan pemerintah, politik, ekonomi, pendidikan, mental, budaya dan teknologi.

Nah pada tulisan blog saya kali ini, saya akan coba membahas dari sisi teknologi. Kira-kira teknologi apa yang bisa diterapkan untuk membantu atau mencegah terjadinya kebakaran hutan. Kebetulan topik ini menjadi salah satu aspek yang saya bahas ketika saya melanjutkan studi S3 Doktoral. Kebetulan (lagi) saya memiliki kesempatan studinya di luar negeri atas beasiswa pemerintah Indonesia. Kebetulan (sekali lagi) saya berada di kota yang cantik dengan di kelilingi kebun anggur terluas dan terpanjang di Perancis. Dan secara geografis, kebun-kebun anggur ini juga memiliki peluang kebakaran juga.

 

Gambaran salah satu penerapan teknologi WSN untuk monitor kebakaran hutan/kebun.

(Sumber: https://research.ece.ncsu.edu/wireless/wsn.html)

 

Wireless Sensor Network (WSN), dalam bahasa Indonesia disebut jaringan sensor nirkabel, adalah salah satu teknologi yang melibatkan sejumlah sensor untuk pemantauan suatu lokasi dengan memanfaatkan teknologi nirkabel yang relatif tidak terlalu mahal. Dalam hal ini, sensor yang akan digunakan adalah sensor panas atau flame sensor.

Saat ini banyak tersedia beberapa tipe sensor. Kalau ga mau pusing yang tinggal beli lalu instal. Tapi pada kenyataannya tidak semudah itu. Coba saja Anda bayangkan. Seandainya Anda ada proyek untuk memonitor 10 hektar kebun anggur atau hutan, (*mudah-mudahan dapat proyek beneran….).  Pertanyaan yang mungkin muncul adalah sebagai berikut:

  1. Berapa jumlah sensor yang diperlukan?
  2. Diletakan dimana sensor-sensor tersebut?
  3. Apakah semua kebun terpantau oleh sensor (coverage)?
  4. Berapa  biaya (cost) yang diperlukan?
  5. Bagaimana dengan infrastruktur jaringan?
  6. Bagaimana dengan konektifitas jaringan?
  7. Bagaimana arsitektur aplikasinya?

Yang mau komentar, kasih masukan & saran silahkan.

Bersambung…..

Colmar, 17/09/2019

IJR Project UMB-UHA-CESI

February 21, 2019

Since October 2017, I have been involving as a member of International Joint Research (IJR) project between 3 institutions (2 France, 1 Indonesian). Currently I’m an associate professor at UMB (maybe until [month] 20[xx] 🙂 ) and a PostDoc fellow at CESI Starsbourg, France, as a part of joint research between UMB-UHA-CESI. We have started our project on December 2017. (more…)

Protokol Routing RPL

January 23, 2018

Internet of Things (IoT) bukan lagi sebagai fantasi sains-fiksi.  Dengan kemajuan teknologi yang sangat pesat memungkinkan terhubungnya semua objek sehari-hari ke Internet. Namun, diperlukan sebuah solusi yang interoperabel untuk memastikan optimal komunikasi antar  objek-objek tersebut. Protokol routing adalah salah satu elemen kunci pada IoT. Karena protokol routing memungkinkan setiap objek menentukan bagaimana mencapai objek lain. Beberapa kendala pada protokol routing antara lain  saluran komunikasi yang tidak stabil dan energi daya rendah yang harus diperhitungkan dalam pengembangan protokol routing yang sesuai untuk IoT.  Pada artikel kali ini, saya akan menyajikan sekilas tentang protokol RPL yang dirancang khusus untuk  jaringan berdaya rendah dan lossy (Low-power and Lossy Network disingkat LLN).

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MATLAB : WSN SIMULATION

November 13, 2017

The instruction is valid for Matlab version R2007b.

First dowload and save grTheory toolobox (save it in Tools): http://www.mathworks.com/matlabcentral/fileexchange/4266. Open the Matlab and go to the File/Set Path and click on the Add Folder. Insert the path to your grTheory toolbox.  (more…)

Optimisasi Penyebaran Jaringan Sensor Pemantauan Maritim Menggunakan Algoritma Genetik

November 8, 2017

Abstrak

Sebagai negara kepulauan terbesar di dunia, Indonesia memiliki potensi besar menjadi poros maritim dunia. Poros maritim merupakan sebuah gagasan strategis yang diwujudkan untuk menjamin konektifitas antar pulau, pengembangan industri perkapalan dan perikanan, perbaikan transportasi laut serta fokus pada keamanan maritim. Maka diperlukan pemantauan maritim untuk mencegah terjadinya hal-hal yang negatif seperti pencemaran laut, pencurian ikan, pelanggaran kedaulatan, sengketa wilayah, dan perompakan. Pemantauan maritim telah menjadi isu yang sangat menarik selama beberapa tahun belakangan ini. Dengan adanya kemajuan teknologi dan Internet yang sangat pesat, teknologi jaringan sensor nirkabel telah menjadi hal yang sangat penting pada pemantauan lingkungan perairan. Penelitian ini mengusulkan sebuah metode optimasi penyebaran jaringan sensor untuk pemantauan lingkungan maritim. Dengan menggunakan pendekatan algoritma genetik multi-obyektif evolusioner untuk mendapatkan solusi topologi jaringan sensor optimal dengan jumlah sensor seminimum mungkin, namun maksimum dalam hal jangkauan dan konektifitas.

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Operator calculus approach for route optimizing and enhancing wireless sensor network

October 1, 2017

This is the abstract of my paper which accepted and published at Journal of Network and Computer Applications,Vol 97, pp. 1-10. 2017. DOI: 10.1016/j.jnca.2017.08.007.

Abstract
Route optimization is one of important feature in wireless sensor networks in order to enhancing the life time of WSNs. Since Centrality is one of the greatest challenges in computing and estimating the important node metrics of a structural graph, it is necessary to calculate and determine the importance of a node in a network. This paper proposes an alternative way to optimizing the route problems which is based on multi-constrained optimal path (MCOP) and operator calculus approach. A novel routing protocol called Path Operator Calculus Centrality (POCC) is proposed as a new method to determine the main path which contains high centrality nodes in a wireless sensor network deployment. The estimation of centrality is using the operator calculus approach based on network topology which provides optimal paths for each source node to base station. Some constraints such as energy level and bit error rate (BER) of node are considered to define the path centrality in this approach. The simulation evaluation shows improved performance in terms of energy consumption and network lifetime.

Keywords
Wireless Sensor Network, Multi-constrained Optimal Path Centrality, Path Centrality, Operator Calculus

NS-2: WSN with obstacles

May 29, 2017

This is the tcl script for simulating a Wireless Sensor Network with some obstacles in the target area.

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Evolutionary Multi-Objective Based Approach for Wireless Sensor Network Deployment

January 14, 2014

Image

Here is the abstract from our paper that already accepted and will be presented on ICC 2014 (International Conference on Communication) that will be held in the beautiful city of Sydney, Australia from 10-14 June 2014.

Abstract: A multi-objective evolutionary algorithm is designed to address some problems in many fields. This paper is a study about deployment strategy for achieving coverage and connectivity as two fundamental issues in wireless sensor networks. To achieve the best deployment, our approach is based on elitist non-dominated sorting genetic algorithm (NSGA-II). There are two objectives in this study, connectivity and coverage. We defined a fitness function to achieved the best deployment of nodes. Further we performed simulation to verify and validate the deployment of wireless sensor network as an output from our proposed mechanism. We measured some performance parameters to investigate and analyze our proposed sensor-deployment. Our simulation results show that our proposed algorithm can maintain coverage and connectivity in given sensing area with a relatively small number of sensor nodes in a given area.

 

How to Installing & Running LEACH on NS-2.34 (Step-by-Step)

May 16, 2012

This is my experience when I installed LEACH on NS-2.34 in my Ubuntu 10.04 LTS. After googling I found some useful links that discussing about how to running Leach on NS-2 as follows :

So here is my note when I installing and running Leach on NS-2.34.  (more…)

Introduction to Wireless Sensor Networks

February 25, 2012

A wireless sensor network is a collection of nodes organized into a cooperative network [10]. Each node consists of processing capability (one or more microcontrollers, CPUs or DSP chips), may contain multiple types of memory (program, data and flash memories), have a RF transceiver (usually with a single omni-directional antenna), have a power source (e.g., batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc fashion. Systems of 1000s or even 10,000 nodes are anticipated. Such systems can  evolutionize the way we live and work.

Currently, wireless sensor networks are beginning to be deployed at an  ccelerated pace. It is not unreasonable to expect that in 10-15 years that the world will be covered with wireless sensor networks with access to them via the Internet. This can be considered as the Internet becoming a physical network. This new technology is exciting with unlimited potential for numerous application areas including environmental, medical, military, transportation, entertainment, crisis management, homeland defense, and smart spaces.

Since a wireless sensor network is a distributed real-time system a natural question is how many solutions from distributed and real-time systems can be used in these new systems? Unfortunately, very little prior work can be applied and new solutions are necessary in all areas of the system. The main reason is that the set of assumptions underlying previous work has changed dramatically. Most past distributed systems research has assumed that the systems are wired, have unlimited power, are not real-time, have user interfaces such as screens and mice, have a fixed set of resources, treat each node in the system as very important and are location independent. In contrast, for wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behavior is important and location is critical. Many wireless sensor networks also utilize minimal capacity devices which places a further strain on the ability to use past solutions.