ORIGINAL ARTICLE Internet of Things process selection: AHP selection method Luiz Fernando C. S. Durão 1 & Marly M. Carvalho 1 & Silvia Takey 2 & Paulo A. Cauchick-Miguel 3 & Eduardo Zancul 1 Received: 15 April 2018 /Accepted: 16 August 2018 # Springer-Verlag London Ltd., part of Springer Nature 2018 Abstract The Internet of Things (IoT) has become an important agenda in the advanced manufacturing environment. In order to encourage IoT application and assure an appropriate selection of processes to be improved by IoT technology, a group of analysis criteria must be highlighted to give the companies a tool to perform the correct selection. This study aims to propose a model for selecting IoT technology. The research design combines a systematic literature review, applying bibliometrics and content analysis, with case application and refinement. An application was carried out in an IoT hardware company, incorporating it at a solvent recycling machine. A second application was performed in a seedling selection machine producer. As a result, a model for selecting IoT technology is presented, which consists of four phases—process modeling, grading, weighting, and final selection. The model applies an analytic hierarchy process (AHP) based on the following criteria: reliability, security, business, mobility, and heterogeneity. The results also suggest IoT selection is related to the ability of combining different criteria related to the system and technology selection to install IoT solutions. Finally, issues related to the system characteristics other than technology are becoming more cited in the literature in the last 5 years concluding that selecting IoT technology is a complex activity that needs to be improved, especially in the years to come. Keywords Internet of Things . IoT . Analytic hierarchy process . AHP . IoT selection criteria 1 Introduction Bridging physical objects and the virtual data environment, the Internet of Things (IoT) provides information about what is actually happening in the real world, in real time [1]. In IoT, things are seamlessly integrated, interconnected, and commu- nicate in any location, being a promising technology for a smart factory, a smart city, etc. [2–4]. However, IoT encom- passes different technologies [5, 6] and “ambiguity stems from the term IoT itself” [7]. Currently available IoT deployments are essentially closed and vertically integrated solutions tai- lored to specific application domains [8]. Considering this need for tailored solutions, different stud- ies proposed criteria for characterized IoT technologies and, thus, to perform an IoT technology selection [3, 9–11]. Some authors highlight sensor search and selection as critical [12], while others focus on integration criteria between the real and digital worlds [ 13 ], and cognitive capability [ 14 ]. Nevertheless, there is still a lack of consensus in the literature mainly because none study provides a definition of a selection model for IoT. Therefore, by narrowing this research gap, this work pro- poses an IoT technology selection model, to answer the fol- lowing research questions: What are the main criteria for selecting IoT technologies? (RQ1) and How are the selection criteria prioritized in tailored solutions in different contexts? (RQ2). A systematic literature review, merging bibliometrics and content analysis [15], was firstly carried out to identify the main criteria that are important for IoT technology selection. Then, analytic hierarchy process (AHP) was applied in two cases: the selection of IoT technologies for a solvent recycler machine by an IoT hardware provider and the selection of IoT technologies for a seedling selection machine by the machine * Eduardo Zancul ezancul@usp.br 1 Department of Production Engineering, Polytechnic School, University of São Paulo, Av. Prof. Almeida Prado, Trav. 2, n. 128, Cidade Universitária, São Paulo 05508-070, Brazil 2 DEV Tecnologia, Av. Prof. Lineu Prestes 2242 – CIETEC – Sala 23, Cidade Universitária, São Paulo 05508-000, Brazil 3 Production Engineering Department, Federal University of Santa Catarina, Campus Universitário Trindade, Caixa Postal 476, Florianópolis 88040-970, Brazil The International Journal of Advanced Manufacturing Technology https://doi.org/10.1007/s00170-018-2617-2