Integration of communication technologies in sensor networks to monitor the Amazon environment Alejandro Cama a , Francisco G. Montoya a , Julio Gómez a , José Luis De La Cruz b , Francisco Manzano-Agugliaro a, * a Department of Engineering, Universidad de Almería, 04120 Almería, Spain b Department of Applied Physics, Universidad de Córdoba, 14071 Campus de Rabanales, Córdoba, Spain article info Article history: Received 27 April 2013 Received in revised form 18 June 2013 Accepted 19 June 2013 Available online 3 July 2013 Keywords: Wireless Sensor Network Amazon 6 LoWPAN Alix Monitoring WiFi abstract Monitoring environmental parameters in the Amazon Rainforest is currently of great significance, as the rainforest actively contributes to the reduction of the climate change impact. The present study dem- onstrates the integration of various communication technologies based on open source software for monitoring environmental parameters in the Peruvian Amazon. The Napo River is a direct tributary of the Amazon River, connecting 450 km in the region of Loreto, Peru. The WiFi network that runs alongside the river is considered the longest in the world. This network will serve as a transport network over which available measurements, including humidity, temperature, total solar radiation (TSR), photosyn- thetically active radiation (PAR), and volumetric water content from the environmental sensors, will be relayed. The linkage between the diverse technologies, from the sensor network to the communication network, and the visualisation on the Internet are explained. The entire project has been planned using low-cost sensors, open source software, and minimal energy consumption. Ó 2013 Elsevier Ltd. All rights reserved. 1. Introduction The importance of maintaining and preserving the Amazon rainforest is deeply related to the impact on the regional hydrology and the global carbon cycle (Nepstad et al., 1994). However, the response of the vegetation to climate variations is poorly under- stood (Jimenez-Munoz et al., 2012). The Amazon rainforest absorbs approximately five billion metric tons of carbon dioxide (CO 2 ) every year. Within its biomass are great carbon reserves (from 70 to 80 billion tons) (Asner et al., 2004). In contrast, the Amazon rainforest reduces the atmospheric concentration of CO 2 because its biosphere contributes to carbon absorption (Cox et al., 2000) and oxygen production through photosynthesis (Peterson and Hustrulid, 1998). Indeed, the Amazon rainforest stores carbon in the vegetation and transforms atmospheric CO 2 to organic carbon via photosynthesis (Mercado et al., 2011). Moreover, CO 2 exerts a direct and instant effect on the environmental temperature (Kirschbaum, 2003). This phenomenon causes variation in the species composition and diversity of the flora (Wittmann et al., 2006). This finding should not be ignored because the Amazon rainforest is the place with the greatest biodiversity on Earth, despite its continuous deforestation during the last several decades (Celentano et al., 2012; Boekhout van Solinge, 2010). One method of contributing to the preservation and mainte- nance of the Amazon rainforest is to permanently monitor the environment, thereby gathering data for subsequent analyses. In this regard, when collection of the environmental data is imple- mented through stationary sensors (data loggers), errors may result when the information is transcribed (Wang et al., 2006). Moreover, this technique is not practical for researchers, as it requires their continuous presence to supervise the periodic measurements. Therefore, due to the morphology and inhospitality of the envi- ronment, the installation of conventional systems of wired sensors is extremely difficult, unrealistic, or even highly inaccessible. For these reasons, Wireless Sensor Networks (WSNs) are suitable for the continuous monitoring of the Amazon rainforest. These devices may be easily deployed, have low costs, are flexible, and support self-organisation (Xue and Hassanein, 2006). Wireless sensor net- works have been deployed in recent years (Bonvoisin et al., 2012; Chong and Kumar, 2003) partially because of the available tech- nology of low cost devices that have low power consumption, which does not limit the computational capabilities for measuring the selected parameters in the region where they are located (Ruiz- * Corresponding author. Tel.: þ34 950015643. E-mail addresses: acp329@alboran.ual.es (A. Cama), pagilm@ual.es (F.G. Montoya), jgomez@ual.es (J. Gómez), fa1crfej@uco.es (J.L. De La Cruz), fmanzano@ual.es (F. Manzano-Agugliaro). Contents lists available at SciVerse ScienceDirect Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro 0959-6526/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jclepro.2013.06.041 Journal of Cleaner Production 59 (2013) 32e42