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

Journal: Sensors (Basel, Switzerland)
PMID:

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.

Authors

  • Alan Kunz Cechinel
    Graduate Program in Automation and System Engineering, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
  • Carlos Eduardo Soares
    Graduate Program in Food Sciences, Federal University of Santa Catarina, Florianópolis 88034-001, SC, Brazil.
  • Sergio Genilson Pfleger
    Graduate Program in Computer Science, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
  • Leonardo Luiz Gambalonga Alves De Oliveira
    Undergraduate Program in Computer Science, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
  • Ederson Américo de Andrade
    Agronomy Department, Federal Institute of Paraná, União da Vitória 84603-264, PR, Brazil.
  • Claudia Damo Bertoli
    Graduate Program in Plant and Animal Science, Catarinense Federal Institute, Camboriú 88340-055, SC, Brazil.
  • Carlos Roberto De Rolt
    Graduate Program in Business Management and Socioeconomic Science-ESAG, State University of Santa Catarina-UDESC, Florianópolis 88035-001, SC, Brazil.
  • Edson Roberto De Pieri
    Graduate Program in Automation and System Engineering, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
  • Patricia Della Méa Plentz
    Graduate Program in Computer Science, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil.
  • Juha Röning
    Biomimetics and Intelligent Systems Group, University of Oulu, P.O. BOX 4500, FI-90014 Oulu, Finland.