Odor Localization using Gas Sensor for Mobile Robot

Husni, Nyayu Latifah; Handayani, Ade Silvia; Nurmaini, Siti; Yani, Irsyadi

doi:10.11591/eecsi.v4.1087

Cited by 4 publications

(6 citation statements)

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“…Furthermore, several cartographic techniques have been developed for individual or multiple robots capable of localizing odor sources. Finally, a simple approach based on a behavioral model has been implemented on a robot fitted with electronic smell and sight in dynamic conditions in order to avoid the high time consumption and rigidity of the algorithm-based approach [11,12].…”

Section: Introductionmentioning

confidence: 99%

An Intelligent IoT-Based Food Quality Monitoring Approach Using Low-Cost Sensors

et al. 2019

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The evolution of multipurpose sensors over the last decades has been investigated with the aim of developing innovative devices with applications in several fields of technology, including in the food industry. The integration of such sensors in food packaging technology has paved the way for intelligent food packaging. These integrated systems are capable of providing reliable information about the quality of the packed products during their storage period. To accomplish this goal, intelligent packs use a variety of sensors suited for monitoring the quality and safety of food products by recording the evolution of parameters like the quantity of pathogen agents, gases, temperature, humidity and storage period. This technology, when combined with IoT, is able to provide a lot more information than conventional food inspection technologies, which are limited to weight, volume, color and aspect inspection. The original system described in this work relies on a simple but effective method of integrated food monitoring, right at the client home, suitable for user prepared vacuum-packed foods. It builds upon the IoT concept and is able to create a network of interconnected devices. By using this approach, we are able to combine actuators and sensing devices also providing a common operating picture (COP) by sharing information over the platforms. More precisely, our system consists of gas, temperature and humidity sensors, which provide the essential information needed for evaluating the quality of the packed product. This information is transmitted wirelessly to a computer system providing an interface where the user can observe the evolution of the product quality over time.

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Section: Introductionmentioning

confidence: 99%

An Intelligent IoT-Based Food Quality Monitoring Approach Using Low-Cost Sensors

et al. 2019

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“…The canonical odor compass is composed of two semiconductor gas sensors mounted to a rotating stage with a fan mounted to draw analyte containing air toward the gas sensors. , Heuristics are used to identify odor source direction by comparing the relative signal from the gas sensors at various rotation angles. , These odor compasses are mounted onto mobile robots so that they can travel through the gas concentration gradient and eventually find the odor source, a process called chemotaxis in the biological context. Often, simple algorithms inspired by Braitenberg vehicles are used, but sophisticated methods for odor source localization have been developed using genetic algorithms, , fuzzy logic, , and infotaxis . Mobile odor compasses have now been used on land, air, , and sea. , …”

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confidence: 99%

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

et al. 2019

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Olfaction is important for identifying and avoiding toxic substances in living systems. Many efforts have been made to realize artificial olfaction systems that reflect the capacity of biological systems. A sophisticated example of an artificial olfaction device is the odor compass which uses chemical sensor data to identify odor source direction. Successful odor compass designs often rely on plume-based detection and mobile robots, where active, mechanical motion of the sensor platform is employed. Passive, diffusion-based odor compasses remain elusive as detection of low analyte concentrations and quantification of small concentration gradients from within the sensor platform are necessary. Further, simultaneously identifying multiple odor sources using an odor compass remains an ongoing challenge, especially for similar analytes. Here, we show that surface-enhanced Raman scattering (SERS) sensors overcome these challenges, and we present the first SERS odor compass. Using a grid array of SERS sensors, machine learning analysis enables reliable identification of multiple odor sources arising from diffusion of analytes from one or two localized sources. Specifically, convolutional neural network and support vector machine classifier models achieve over 90% accuracy for a multiple odor source problem. This system is then used to identify the location of an Escherichia coli biofilm via its complex signature of volatile organic compounds. Thus, the fabricated SERS chemical sensors have the needed limit of detection and quantification for diffusion-based odor compasses. Solving the multiple odor source problem with a passive platform opens a path toward an Internet of things approach to monitor toxic gases and indoor pathogens.

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“…Seperti pada aplikasi mobile robot dalam pencari target sumber gas dengan memanfaatkan sensor pendukungnya seperti sensor gas yang dilakukan oleh Albornoz dkk [2], dan dengan penambahan kamera wireless oleh Herjuno dkk [3]. Nurmaini dkk [4] dan Husni dkk [5] juga membahas pencarian target aroma gas berbasis mobile robot dengan navigasi cerdas menggunakan fuzzy logic. Penggunaan fuzzy logic memberikan kemudahan dalam pengambilan keputusan berdasarkan pengalaman.…”

Section: Pendahuluanunclassified

“…Selanjutnya mengkonversi dari keluaran fuzzy menjadi keluaran crisp. Metode konversi ini menggunakan Centroid [5], [11]. Nilai crisp ini ditransfer pada modul driver untuk mengendalikan kecepatan putar motor kiri dan kanan.…”

Section: Tahap Defuzzifikasiunclassified

Implementasi Fuzzy Logic dan Trajectory Pada Manipulator Mobile Robot Untuk Deteksi Kebocoran Gas

Rendyansyah

Prasetyo

Exaudi

2019

JRE

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Teknologi yang berkembang dapat mempermudah aktivitas pekerjaan, salah satunya teknologi di bidang robotik. Salah satu tujuan robot diciptakan untuk membantu dalam investigasi target yang dicurigai. Target tersebut dapat berupa objek kebocoran sumber gas. Di sisi lain, kebocoran gas dalam kawasan industri mengakibatkan dampak yang besar bagi lingkungan. Robot sangat diperlukan untuk mempermudah dalam proses inspeksi target yang diduga kebocoran gas. Robot pada umumnya memiliki sistem yang terintegrasi dengan sensor sebagai interface dan komputasi cerdas. Pada penelitian ini telah dirancang mobile robot dan manipulator yang terintegrasi dan memiliki tujuan untuk menginspeksi objek yang diduga kebocoran gas. Sistem robot ini disebut manipulator mobile robot yang dilengkapi dengan kamera wireless untuk deteksi objek, dua buah sensor gas untuk deteksi aroma, masing-masing sensor dipasang pada end-effector manipulator dan di samping kamera. Adapun metode yang digunakan pada robot yaitu fuzzy logic dan cubic trajectory. Fuzzy logic digunakan untuk navigasi robot menuju objek, dan cubic trajectory untuk navigasi manipulator berdasarkan rute yang ditentukan. Pada percobaan yang telah dilakukan, mobile robot dapat bernavigasi menuju target sampai berhenti pada jarak 20cm, dan manipulator juga berhasil dalam bernavigasi. Dalam instrumen pengujian, telah ditentukan dua titik bocor. Masing-masing titik diuji sebanyak enam kali. Adapun robot berhasil dalam mendeteksi kebocoran gas dengan keberhasilan mencapai 91,67%, dan posisi koordinat yang terbaca oleh manipulator dapat diamati melalui monitor.

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Odor Localization using Gas Sensor for Mobile Robot

Cited by 4 publications

References 0 publications

An Intelligent IoT-Based Food Quality Monitoring Approach Using Low-Cost Sensors

An Intelligent IoT-Based Food Quality Monitoring Approach Using Low-Cost Sensors

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens

Implementasi Fuzzy Logic dan Trajectory Pada Manipulator Mobile Robot Untuk Deteksi Kebocoran Gas

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