In this paper, a detailed review of microcontroller unit (MCU)-based wireless sensor node platforms from recently published research articles is presented. Despite numerous research efforts in the fast-growing field of wireless sensor devices, energy consumption remains a challenge that limits the lifetime of wireless sensor networks (WSNs). The Internet-of-Things (IoT) technology utilizes WSNs for providing an efficient sensing and communication infrastructure. Thus, a comparison of the existing wireless sensor nodes is crucial. Of particular interest are the advances in the recent MCU-based wireless sensor node platforms, which have become diverse and fairly advanced in relation to the currently available commercial WSN platforms. The recent wireless sensor nodes are compared with commercially available motes. The commercially available motes are selected based on a number of criteria including popularity, published results, interesting characteristics and features. Of particular interest is to understand the trajectory of development of these devices and the technologies so as to inform the research and application directions. The comparison is mainly based on processing and memory specifications, communication capabilities, power supply and consumption, sensor support, potential applications, node programming and hardware security. This paper attempts to provide a clear picture of the progress being made towards the design of autonomous wireless sensor nodes to avoid redundancy in research by industry and academia. This paper is expected to assist developers of wireless sensor nodes to produce improved designs that outperform the existing motes. Besides, this paper will guide researchers and potential users to easily make the best choice of a mote that best suits their specific application scenarios. A discussion on the wireless sensor node platforms is provided, and challenges and future research directions are also outlined.

In Sub-Saharan Africa, where most irrigation systems are manually operated, water allocation and irrigation scheduling are often based on uniform application irrespective of crop needs and growth stages, which results in nonoptimal water use. Recently, a lot of research has been carried out to improve irrigation water use efficiency through automation by employing wireless sensor-based monitoring systems. Further to the improvement of water use efficiency and yield, while reducing costs, a field trial was carried out at a farm in Harare, Zimbabwe, during the 2016, 2017, and 2018 winter seasons to test whether a new approach to the automated irrigation systems, one based on IoT and wirelessly connected soil sensors (called hereafter as WCSS), improves water use efficiency without reducing yield. WCSS method was compared with three widely used conventional irrigation methods, that is, manual scheduling, tensiometer-based scheduling, and weather-based scheduling. Impacts on water savings and yield of winter wheat crops under drip irrigation were evaluated. WCSS saved up to 25% more water compared to typical fixed irrigation schedule rates used by wheat growers during the winter season.