Analysis of voltage–current behavior of photovoltaic modules is a critical part of their modeling. Parameter identification of these models demands data from them, measured in realistic environments. In spite of advancement in modeling methodologies under solar lighting, few analyses have been focused on indoor photovoltaics. Lack of accurate and reproducible data as a major challenge in this field is addressed here. A high accuracy measurement setup for evaluation and analysis of indoor photovoltaic modules is explained. By use of this system, different modules are measured under diverse environmental conditions. These measurements are structured in data-sets that can be used for either analysis of physical environment effects and modeling or development of specific parameter identification methods in low light intensity conditions.

Understanding dynamic behavior of a battery and the possibility of simulating it is necessary during design of IoT systems. This plays a critical role, especially for industrial devices with low-power demands planned for long lasting operation. While cost limitation mostly leads to use of the low-budget batteries with fast degradation, a model of these batteries supplying low-power loads is provided here. The overall model is in open-loop form because no access to the terminal measurements is available during the design phase. The identification process of the relation between the state of charge and related electromotive force as a key element of the model is discussed. Moreover, guidelines are suggested for identification of this relation. Furthermore, SoC estimation based on the Coulomb counting is modified to include a dynamic inter-cycle aging factor. This factor enables replication of the degradation within a single cycle. In spite of simplicity of this concept, it is able to reduce the model’s estimation error evaluated with two different types of loads. The overall model provides promising results with relative errors less than 0.2%.

Future warehouses will be made of modular embedded entities with communication ability and energy aware operation attached to the traditional materials handling and warehousing objects. This advancement is mainly to fulfill the flexibility and scalability needs of the emerging warehouses. However, it leads to a new layer of complexity during development and evaluation of such systems due to the multidisciplinarity in logistics, embedded systems, and wireless communications. Although each discipline provides theoretical approaches and simulations for these tasks, many issues are often discovered in a real deployment of the full system. In this paper we introduce PhyNetLab as a real scale warehouse testbed made of cyber physical objects (PhyNodes) developed for this type of application. The presented platform provides a possibility to check the industrial requirement of an IoT-based warehouse in addition to the typical wireless sensor networks tests. We describe the hardware and software components of the nodes in addition to the overall structure of the testbed. Finally, we will demonstrate the advantages of the testbed by evaluating the performance of the ETSI compliant radio channel access procedure for an IoT warehouse.