scholarly journals Development of an Open-Source Cloud-Connected Sensor-Monitoring Platform

2018 ◽  
Vol 08 (01) ◽  
pp. 1-11 ◽  
Author(s):  
Daniel K. Fisher ◽  
Reginald S. Fletcher ◽  
Saseendran S. Anapalli ◽  
H. C. Pringle III
Keyword(s):  
Open Source ◽  
Sensor Monitoring ◽  
Monitoring Platform

scholarly journals Open source arc analyzer: Multi-sensor monitoring of wire arc additive manufacturing

HardwareX ◽  
2020 ◽  
Vol 8 ◽  
pp. e00137
Author(s):  
Adam M. Pringle ◽  
Shane Oberloier ◽  
Aliaksei L. Petsiuk ◽  
Paul G. Sanders ◽  
Joshua M. Pearce
Keyword(s):  
Additive Manufacturing ◽  
Open Source ◽  
Sensor Monitoring ◽  
Wire Arc Additive Manufacturing

scholarly journals Internet of Things Platform for Manage Multiple Message Queuing Telemetry Transport Broker Server

2019 ◽  
pp. 197-206 ◽  
Author(s):  
Aulia Arif Wardana ◽  
Andrian Rakhmatsyah ◽  
Agus Eko Minarno ◽  
Dhika Rizki Anbiya
Keyword(s):  
Internet Of Things ◽  
Response Time ◽  
Open Source ◽  
Business Process ◽  
Usability Testing ◽  
Recording System ◽  
The Other ◽  
The Internet ◽  
The Internet Of Things ◽  
Monitoring Platform

This study proposed the Internet of Things (IoT) monitoring platform model to manage multiple Message Queuing Telemetry Transport (MQTT) broker server. The Broker is a part of the MQTT protocol system to deliver the message from publisher to subscriber. The single MQTT protocol that setup in a server just have one broker system. However, many users used more than one broker to develop their system. One of the problems with the user that use more than one MQTT broker to develop their system is no recording system that helps users to record configurations from multi brokers and connected devices. This can cause to slow the deployment process of the device because the configuration of the device and broker not properly managed. The platform built is expected to solve the problem. This proposed platform can manage multiple MQTT broker server and device configuration from different product or vendor. The platform also can manage the topic that connects to a registered broker on the platform. The other advantages of this platform are open source and can modify to a specific business process. After usability testing and response time testing, the proposed platform can manage multiple MQTT broker server, functional to use, and an average of response time from the platform page is not more than 10 seconds.

scholarly journals Accurate Identification of Agricultural Inputs Based on Sensor Monitoring Platform and SSDA-HELM-SOFTMAX Model

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Juan Zou ◽  
Hanjing Jiang ◽  
Qingxiu Wang ◽  
Ningxia Chen ◽  
Ting Wu ◽  
...  
Keyword(s):  
Accurate Identification ◽  
Detection Techniques ◽  
Discriminant Model ◽  
Artificial Intelligence Algorithm ◽  
Input Monitoring ◽  
Learning Machine ◽  
Agricultural Input ◽  
Hardware Circuit ◽  
Sensor Monitoring ◽  
Monitoring Platform

The unreliability of traceability information on agricultural inputs has become one of the main factors hindering the development of traceability systems. At present, the major detection techniques of agricultural inputs were residue chemical detection at the postproduction stage. In this paper, a new detection method based on sensors and artificial intelligence algorithm was proposed in the detection of the commonly agricultural inputs in Agastache rugosa cultivation. An agricultural input monitoring platform including software system and hardware circuit was designed and built. A model called stacked sparse denoising autoencoder-hierarchical extreme learning machine-softmax (SSDA-HELM-SOFTMAX) was put forward to achieve accurate and real-time prediction of agricultural input varieties. The experiments showed that the combination of sensors and discriminant model could accurately classify different agricultural inputs. The accuracy of SSDA-HELM-SOFTMAX reached 97.08%, which was 4.08%, 1.78%, and 1.58% higher than a traditional BP neural network, DBN-SOFTMAX, and SAE-SOFTMAX models, respectively. Therefore, the method proposed in this paper was proved to be effective, accurate, and feasible and will provide a new online detection way of agricultural inputs.

Open Source

2007 ◽  
Author(s):  
Fadi P. Deek ◽  
James A. M. McHugh
Keyword(s):  
Open Source
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