## 1 Introduction  
It is projected that networked microsensor technology, in the form of Wireless Sensor Networks (WSNs), will keep playing an important role in the future of remote sensing [1]. Some of the applications for WSNs range from automation, human monitoring, equipment condition monitoring, defense, aerospace, building, structural health monitoring and agriculture [2; 3; 4; 5; 6]. As reported in [7], WSNs have been implemented in point-to-multipoint and local point-to-point communication networks achieving long-term field deployment but a limited sensing-data processing. However, WSNs are nowadays increasingly becoming part of a more pervasive concept, the Internet of Things (IoT), which allows devices to communicate with each other and collect information on a much larger scale through the internet [8]. This opens new possibilities to achieve more comprehensive data processing of the information being collected. IoT has the potential to foster a large number of applications by enabling more devices to be connected to the web and make use of a wider range of pre-collected and pre-processed data. A paramount challenge that can pose a limitation for a wider adoption in the use of IoT smart nodes in areas of difficult access, is inherently associated to its battery requirements for a considerable power specification needed to perform on-field sensor measurements and to send the collected information to the cloud. A desirable feature of WSN is to minimize not only the size and cost of the energy storage element itself, but also to reduce the maintenance needed to constantly replace the sensor's batteries. Harvesting enough energy from the environment where the WSN is physically located, can be a plausible solution to extend the battery life of a remote sensor and even fully power it for prolonged periods of time [9; 10]. The sources of energy that can be harvested from the ambient include solar, kinetic, thermal gradient, radiofrequency, electromagnetic and Microbial Fuel Cells (MFCs) [11; 12; 13; 14; 15; 16]. MFCs are a promising emerging source of energy harvesting that can transform organic and inorganic matter to generate electricity by using a bioelectrochemical conversion process [17; 18; 19; 20; 21]. MFCs can find a particular application in remote sensing [22] for places that are difficult to access routinely for maintenance but with abundant organic material available, such as sewage water and even oceans [23; 24; 25], where the use and replacement of batteries, can be costly or impractical [26; 27; 28; 29; 30; 16]. A potential application that can combine IoT devices and MFC technologies is in the management and optimization of traditionally public services, such as residual water treatment plants [31]. It is important to note that while MFCs can generate power from liquid and organic sediments found in wastewater and oceans, smart nodes can monitor and transmit conditions found in water being treated, such as temperature, pH, conductivity, salinity, and organic sediment concentration, to name a few [23; 24; 25; 32]. Despite these opportunities, one of the main limitations of energy harvesting from MFC technologies is the low output power levels provided by each individual cell, typically in the order of microwatts to a few milliwatts per liter [33]. For this reason, a Power Management System (PMS) is required to maximize the power conversion efficiency and increase the voltage and current level to the nominal power levels required by wireless sensors. Some implementations of PMS have previously been reported to maximize the energy harvesting efficiencies of single MFCs [23; 28; 29; 30; 34; 35; 36]. To reach usable output voltage levels while at the same time increasing the output current density is by connecting several MFCs in series or in parallel to increase the overall power out level.