Internet of Things and autonomous control for vertical cultivation walls towards smart food growing: A review

The development of green spaces in urban areas is rapidly on the rise as more people are keen to maintain a clean and green atmosphere around where they live and work. Also, the link between the physical world and the internet has been a driving force in enhancing people's quality of life which has resulted in the most recent and rising technologies, collectively referred to as the Internet of Things (IoT). The adoption of vertical gardens (VG) and/or vertical farms (VF) can be beneficial for maintaining a sustainable environment, as well as for expanding food security in an urban context around the world with limited land space. IoT technologies have the potential to be key enablers in the accelerated adoption of VG. In this study, we investigate the critical parameters for automating sustainable vertical gardening systems by using the IoT concept in smart cities towards smart living. This involves collection and review of data from 30 peer-reviewed publications published between 2004 and 2018, including real-world VG implementations. The key criteria considered include: (i) crop/plant type, (ii) VG topology (size), (iii) sensing data, (iv) used hardware (sensors, actuators, etc.), (v) power supplies, (vi) velocity or frequency of data collection, (vii) data storage method, (viii) communication technologies, (ix) data analysis methods/algorithm, (x) other used strategies, and (xi) countries that implemented VGs. The data were subsequently analyzed to obtain a detailed understanding of using IoT in VGs. The results of the analysis revealed that most of the studies used 6-20 tiers (40%) when implementing VGs, and the most popular crop was lettuce (28.6%). The sensors used were commonly connected to AC power and battery (each 44.4%), while only a small proportion of VGs used solar power (11.1%). The majority of IoT sensors used were to measure room temperature (22.5%), light intensity (21.1%), humidity level (14%) and soil nutrition (7%). The frequency of data collection by these sensors was between 1 and 3 minutes (42.8%). The frequently used data transmission technology was Zigbee and Wi-Fi (42.8%) for collecting sensor data from VGs. We also found that, using the server database, remote data management platform and cloud were the most popular data storage methods (each 25%). After data collection, many studies used threshold-based algorithms (50%) for the decision making, and the soil-based (42%) and hydroponic (38%) were the most popular plant cultivatio