Summary This article presents a power management system (PMS) designed for smart homes aiming to deal with the new challenges imposed by the proliferation of plug‐in electric vehicles (EVs) and their coexistence with other residential electrical appliances. The PMS is based on a hybrid wireless network architecture composed by a local hub/gateway and several Bluetooth Low Energy (BLE) and Wi‐Fi sensor/actuator devices. These wireless devices are used to transfer information inside the smart home using the Message Queuing Telemetry Transport (MQTT) protocol. Based on the proposed solution, the current consumption of the EV battery charger and other residential electrical appliances are dynamically monitored and controlled by using a configurable algorithm, ensuring that the total current consumption does not cause the tripping of the home circuit breaker. An Android client application allows the user to monitor and configure the system operation in real‐time, a developed Wi‐Fi smart plug permits to measure the RMS values of current of the connected electrical appliance and change its state of operation remotely, and an EV battery charger may be controlled in terms of operating power according to set‐points received from the Android client application. Experimental tests are used to evaluate the quality of service provided by the developed smart home platform in terms of communication delay and reliability. An experimental validation for different conditions of operation of the proposed smart home PMS concerning the power operation of the EV battery charger with the proposed control algorithm is also presented.

This work describes the development and evaluation of two smart home-based Internet of Things (IoT) systems applied to HVAC (Heating, Ventilation and Air Conditioning) monitoring and control, including parameters such as temperature, humidity, air quality, smoke detection, and human presence. These systems are based on a flexible hybrid wireless network architecture combining Bluetooth Low Energy (BLE) and IEEE 802.11/Wi-Fi, in order to adapt to the requirements of different types of sensor and actuator devices. The original implemented network is based on Cypress PSoC 4 BLE boards and HyperText Transfer Protocol (HTTP), whereas the new network uses ESP32 boards and includes Message Queue Telemetry Transport (MQTT), a lightweight messaging protocol suitable for IoT devices which provides additional quality of service (QoS) mechanisms to guarantee the delivery of messages. A smart temperature control system was implemented in the BLE/Wi-Fi gateway (Raspberry Pi) to keep the room temperature inside a user-defined range. An online database was also developed using the Amazon Web Services (AWS) cloud platform, allowing the users to access the HVAC data and control the system parameters, through the Internet, using a mobile app developed for Android devices. Experimental tests were performed to validate the functionalities and performance of the developed systems. The obtained results demonstrate that the new network provides lower delay values compared with the original implementation.

LiDAR (Light Detection And Ranging) is a technology used to measure distances to objects. Internally, a LiDAR system is constituted by several components, including a power supply, which is responsible to provide the distinct voltage levels necessary for all the components. In this context, this paper presents an efficiency comparison of three different DC-DC converter architectures for a LiDAR system, each one composed of three DC-DC converters: in parallel; in cascade; and hybrid (mix of parallel and cascade). The topology of the adopted integrated DC-DC converters is the synchronous buck Switched-Mode Power Supply (SMPS), which is a modified version of the basic buck SMPS topology. Three distinct SMPSs were considered: LM5146-Q1, LM5116, and TPS548A20RVER. These SMPSs were selected according to the requirements of voltage levels, namely, 12 V, 5 V, and 3.3 V. Along the paper, the principle of operation of the SMPSs is presented, as well as the evaluation results obtained for different operating powers, allowing to establish a comprehensive efficiency comparison.

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Smart cities integrate a wide and diverse set of small electronic devices that use Internet communication capabilities with very different purposes and features. A challenge that arises is how to feed these small devices. Among the various possibilities, energy harvesting presents itself as the most economical and sustainable. This paper describes the design and simulation of an electronic circuit dedicated to maximizing the solar power extraction from photovoltaic (PV) modules. For this purpose, an integrated circuit (IC) dedicated to energy harvesting is used, namely the LTC3129. This IC is a DC-DC converter that uses the maximum power point control (MPPC) technique, which aims to keep its input voltage close to a defined reference value. The designed circuit is used with three photovoltaic modules, each one of a different PV technology: monocrystalline silicon, polycrystalline silicon and amorphous silicon. These PV modules are installed in a weather station to correlate the power produced with the meteorological conditions, in order to assess which solar photovoltaic technology is best for a given location. The equivalent circuit of a solar cell is used in simulation to represent a photovoltaic module. The values of the components of the equivalent circuit are adjusted so they have the same characteristics of the modules installed in the weather station. With each module, a power resistor of the same value is used as load, for comparison purposes. For the case of the monocrystalline silicon technology, the use of the LTC3129 converter increases the power extraction by 47.6% compared to when this converter is not used between the PV module and the load.