## 1 Introduction  
Most of the perishable food to be exported requires several transportation days to reach the destination. To preserve quality of the transported products, recommended environmental conditions are required [1]. According to FAO (2019) [2], 1.3 billion tons are annually wasted, corresponding to more than 30% of all the food produced, from which approximately 50% are fruit and vegetables. These data are unsustainable in our society and require an effort to minimize these extremely high food losses. New technologies such as Internet of Things (IoT) and artificial intelligence (AI) used during the postharvest supply chain would allow us to know more precisely where these losses occur and propose actions to minimize them [3, 4, 5]. Temperature is the most important environmental factor to be preserved between certain recommended values during the postharvest stages [6]. Many works have related the evolution of the temperature of the perishable commodities with the quality losses, obtaining representative models that allow for predicting the shelf life [7, 8, 9, 10, 11]. Shelf life is the time in which a food product remains at high-quality standards while being micro-biologically safe [12]. These models allow for estimating commodities' shelf life based on the temperature data recorded during the postharvest stages [13]. Several suppliers provide devices able to record temperature data for a long time (months or years). Small card-shaped devices with USB connection are one of the most frequently used as temperature loggers during transport or other postharvest periods [14, 15]. Other devices such as time temperature integrators (TTI) are also used to show temperature preservation during a certain period [16]. Radio frequency identification (RFID) and IoT technologies, such as Bluetooth or NFC, are recently being used to distribute sensors inside pallets or cardboard boxes, making it possible to determine the temperature variation between different areas of the same load [17], providing an either efficient or not pallet distribution [18; 19] The time-temperature data registered by these portable and autonomous devices are downloaded at the destination for temperature abuse detection. A brief review is detailed in Section 2. Quality standards and consumer requirements, as well as the necessary guarantee by the transporter to ensure the correct logistical handling of the commodities, means that this sector demands precise, autonomous and flexible devices that are capable of data recording and real-time reporting those variables that influence the dynamic shelf life of a perishable product, as defined by postharvest technology. Even though the temperature is the main factor, other environmental variables such as relative humidity, luminosity, vibrations and physiological active gases such as oxygen (O2), carbon dioxide (CO2) and C2H4 (ethylene) influence the quality degradation processes, most of them resulted to maturation, so that their detection and control throughout the postharvest supply chain determines optimal preservation conditions [20]. Wireless sensor network (WSN) platforms have been widely used in placements where a high density and an intelligent allocating of sensors is required for precision measurement [21]. Areas such as precision agriculture [22; 23], oceanography [24] and home automation [25; 26; 27] use IoT technology and cloud solutions [28; 29] to deploy collaborative sensor networks. This WSN collects the information of the several nodes and routes the data to the Internet by using some of the protocols available such as GSM/GPRS, NoB-IoT, SigFox, LoRa, etc., which provide real-time access to the data.