## 4 Bibliographic Analysis  
A more comprehensive and systematic bibliometric analysis has been conducted considering the online abstract and indexing service provided by Scopus(r) from Elsevier. The reason for its choice--as opposed to others, such as the IEEE Xplore(r) digital library, Google Scholar, ResearchGate, ArXiv, or DBLP--is that Scopus(r) is considered the world's largest scientific database. Furthermore, Scopus(r) is available for free and has also been used in many previous bibliometric analyses [129; 130; 131; 132]. The search range was focused on the period from 1997 to 2018 and performed with the following structure: TITLE-ABS-KEY (\"_term_1\" OR \"_term_2\" OR \"_term_n\"_ AND \"_term_i\"_ [...] AND NOT \"_term_j\"_ [...]) AND (LIMIT-TO (SUBJAREA, \"COMP\") OR LIMIT-TO (SUBJAREA, \"ENGI\")) AND (EXCLUDE (PUBYEAR, 2019)). The publications were gathered to compare whole annual periods, limited to the categories of Computer Science and Engineering, then filtered to avoid the misuse of terms belonging to other disciplines (i.e., acronyms with various meaning) and finally processed using spreadsheets to sort the results. The publications in Scopus(r) were evaluated considering the following factors: Number of manuscripts per year, source type, keywords, country, and affiliation of the authors. Note that the analysis made in this section has no potential bias, since all the manuscripts stored in Scopus(r) have been entirely considered unlike the previous section. _Evolution of Mobile Devices, Sensors, and Intelligent Applications for Smart Cities_  
Regarding the technological context, the sample analyzed in this work included 10,867 articles within the \"Smart City\" category, 35,537 for \"WSN\", 41,485 for \"Internet of Things\", 19,475 for \"Smartphone\", and 3422 for \"I2X, V2X, P2X\" and their variants (Figure 4). The survey showed a recent research in all fields in general with a major disruption of the \"Internet of Things\" (37.4%) over \"WSN\" (32.1%), \"Smartphone\" (17.6%), \"Smart City\" (9.81%), and \"I2X, V2X, and P2X\" (3.31%). A comparison between the evolution of the publications showed an outstanding correlation for \"Smart City\" versus \"Internet of Things\" (\(r^{2}=0.967\), \(p<<0.01\)). The analysis also showed a good correlation for \"Smartphone\" versus \"I2X, V2X, and P2X\" (\(r^{2}=0.881\), \(p<<0.05\)), \"Internet of Things\" versus \"I2X, V2X, and P2X\" (\(r^{2}=0.878\), \(p<<0.05\)), and \"Smart City\" versus \"I2X, V2X, and P2X\" (\(r^{2}=0.809\), \(p<<0.05\)). On the contrary, the bibliographic evolution showed a lower association in the publications of \"WSN\" versus \"Internet of Things\" (\(r^{2}=0.279\), \(p=0.013\)) and \"Smart City\" versus \"WSN\" (\(r^{2}=0.295\), \(p=0.008\)). This study suggests that the I2X, V2X, and P2X technologies are strongly related to smart cities, IoT, and smartphones. At the far side, WSN is less related with IoT and smart cities. An analysis on the publications per territory focused specifically on I2X, V2X, and P2X communications showed significant activity mainly in Asia (39.65%), Europe (32.25%), and North America (20.55%), followed by South America, Africa, and Oceania to a lesser extent (7.53%). A study on the most productive countries and their relationship was then conducted. To this end, VOSviewer was chosen as the software tool for creating, visualizing, and exploring maps based on network data [133]. The results are resumed in Figure 5 and Table 1 for which thesaurus files and the Lin-Log clustering technique were used to filter inconsistencies over a total of 80 countries. Figure 4: Evolution of key technologies for mobile devices, sensors, and intelligent applications in smart cities. Figure 5: Cooperation between countries based on the publication co-authorship from 1996 to 2018. A study about the distribution of the organizations showed the leadership of universities (74.48%) over research institutions (15.85%) and private corporations (9.65%).