Development of internet of things carbon-based nanomaterial sensors for smart plant growth system

Name: Gun Chaloeipote

LCSH: Kasetsart University -- Dissertations. Ph.D. (Physics) 2021

Classification :.LCCS: QC611.6.Q35

LCSH: Kasetsart University. -- Department of Physics -- Dissertations

LCSH: Quantum dots

LCSH: Graphene

LCSH: Copper oxide

LCSH: Silver

LCSH: Nanocomposites (Materials)

LCSH: Internet of things

LCSH: Nanostructured materials

Abstract: This thesis proposes a low-cost, fast and simple fabrication of resistive-type humidity sensors based on the graphene quantum dots (GQDs) and silver nanoparticles (AgNPs) nanocomposites synthesized by hydrothermal method and green reducing agent route, respectively. The structural characterization results presented core/shell-like structure. According to sensing results, the ratio of GQDs/AgNPs 1:1 exhibits the best humidity response at room temperature and faster response/recovery times than commercial one at the same condition. The sensing mechanism of the GQDs/AgNPs humidity sensor is proposed via Schottky junction formation and intrinsic synergistic effects. Moreover, a room-temperature ammonia gas sensor based on n-type copper oxide (CuO) semiconductor was fabricated by 3D printing technique. The structural characterization results of 3D printed sensor showed monoclinic CuO phase and scaffold structures. According to gas-sensing data, the 3D printed CuO gas sensor exhibited good repeatability, high stability, low humidity dependency, high sensitivity and selectivity towards ammonia at room temperature. The sensing mechanism of the 3D printed CuO sensor was proposed based on the resistance change via reaction on adsorbed surface oxygen species or direct electron transfer between ammonia molecules and CuO. Furthermore, this thesis is also focused on development of IoT digital home farm to manage plant growth and aquatic animal for household users. The obtained data from sensing measurement can be sent notifications to user’s mobile application in real-time for operation by manual or automatic function.

Kasetsart University. Office of the University Library

Address: Bangkok

Email: tdckulib@ku.ac.th

Name: Chatchawal Wongchoosuk

Role: Thesis Advisor

Created: 2021

Modified: 2025-07-12

Issued: 2025-07-12

วิทยานิพนธ์/Thesis

application/pdf

URL: https://www.lib.ku.ac.th/KUthesis/2564/gun-cha-all.pdf

CallNumber: QC611.6.Q35 .G86

eng

DegreeName: Doctor of Philosophy

Level: Doctoral Degraee

Descipline: Physics

Grantor: Kasetsart University

©copyrights Kasetsart University

ลำดับที่.	ชื่อแฟ้มข้อมูล	ขนาดแฟ้มข้อมูล	จำนวนเข้าถึง	วัน-เวลาเข้าถึงล่าสุด
1	gun-cha-all.pdf	5.22 MB	1	2025-07-25 12:19:32

ใช้เวลา

0.018234 วินาที