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移动机器人+物联网:用于肉鸡粪便消毒的可持续技术项目。

Mobile Robot + IoT: Project of Sustainable Technology for Sanitizing Broiler Poultry Litter.

机构信息

Graduate Program in Automation and System Engineering, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.

Graduate Program in Food Sciences, Federal University of Santa Catarina, Florianópolis 88034-001, SC, Brazil.

出版信息

Sensors (Basel). 2024 May 11;24(10):3049. doi: 10.3390/s24103049.

DOI:10.3390/s24103049
PMID:38793903
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11125414/
Abstract

The traditional aviary decontamination process involves farmers applying pesticides to the aviary's ground. These agricultural defenses are easily dispersed in the air, making the farmers susceptible to chronic diseases related to recurrent exposure. Industry 5.0 raises new pillars of research and innovation in transitioning to more sustainable, human-centric, and resilient companies. Based on these concepts, this paper presents a new aviary decontamination process that uses IoT and a robotic platform coupled with ozonizer (O) and ultraviolet light (UVL). These clean technologies can successfully decontaminate poultry farms against pathogenic microorganisms, insects, and mites. Also, they can degrade toxic compounds used to control living organisms. This new decontamination process uses physicochemical information from the poultry litter through sensors installed in the environment, which allows accurate and safe disinfection. Different experimental tests were conducted to construct the system. First, tests related to measuring soil moisture, temperature, and pH were carried out, establishing the range of use and the confidence interval of the measurements. The robot's navigation uses a back-and-forth motion that parallels the aviary's longest side because it reduces the number of turns, reducing energy consumption. This task becomes more accessible because of the aviaries' standardized geometry. Furthermore, the prototype was tested in a real aviary to confirm the innovation, safety, and effectiveness of the proposal. Tests have shown that the UV + ozone combination is sufficient to disinfect this environment.

摘要

传统的禽舍消毒过程涉及农民将农药施用于禽舍地面。这些农业防御措施很容易在空气中扩散,使农民容易患上与反复接触相关的慢性疾病。工业 5.0 在向更可持续、以人为本和有弹性的公司转型方面提出了新的研究和创新支柱。基于这些理念,本文提出了一种新的禽舍消毒工艺,该工艺使用物联网和机器人平台,并结合臭氧发生器 (O) 和紫外线灯 (UVL)。这些清洁技术可以成功地对家禽养殖场进行消毒,以对抗病原体微生物、昆虫和螨虫。此外,它们还可以降解用于控制生物的有毒化合物。这种新的消毒工艺通过安装在环境中的传感器利用禽粪中的物理化学信息,从而实现精确和安全的消毒。进行了不同的实验测试来构建该系统。首先,进行了与测量土壤湿度、温度和 pH 值相关的测试,确定了使用范围和测量的置信区间。机器人的导航使用与禽舍最长边平行的来回运动,因为这可以减少转弯次数,从而降低能耗。由于禽舍的标准化几何形状,这项任务变得更加容易。此外,还在实际的禽舍中对原型进行了测试,以确认该方案的创新性、安全性和有效性。测试表明,紫外线+臭氧的组合足以对这种环境进行消毒。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/602cefe1cc0a/sensors-24-03049-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/49779e441b0b/sensors-24-03049-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/35a8994a6857/sensors-24-03049-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/41482a0131d2/sensors-24-03049-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/af3f7d3f873c/sensors-24-03049-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/6d18c1779723/sensors-24-03049-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/651e5dd5f336/sensors-24-03049-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/8b752bac4d3c/sensors-24-03049-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/602cefe1cc0a/sensors-24-03049-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/49779e441b0b/sensors-24-03049-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/35a8994a6857/sensors-24-03049-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/41482a0131d2/sensors-24-03049-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/af3f7d3f873c/sensors-24-03049-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/6d18c1779723/sensors-24-03049-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/651e5dd5f336/sensors-24-03049-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/8b752bac4d3c/sensors-24-03049-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2f/11125414/602cefe1cc0a/sensors-24-03049-g008.jpg

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