Rate My Professor Scott Fazackerley

His research specializations encompass embedded systems, wireless sensor networks, flash memory optimization for memory-constrained devices, IoT applications, precision agriculture, data logging, automation, sensor technology, and time series indexing for agricultural and environmental monitoring. Key publications include 'Space-efficient B-tree Implementation for Memory-Constrained Flash Embedded Devices' (2026), 'An Efficient B-tree Implementation for Memory-Constrained Embedded Systems' (2023), 'Practical Precision Agriculture with LoRa based Wireless Sensor Networks' (2021), 'Efficient Flash Indexing for Time Series Data on Memory-constrained Embedded Sensor Devices' (2021), 'A flash resident file system for embedded sensor networks' (2011), 'Automatic in situ determination of field capacity using soil moisture sensors' (2012), and 'Cluster head selection using RF signal strength' (2009). He teaches courses such as COSC 328 and was recognized as an Outstanding Instructor for 2024/25 in the Irving K. Barber Faculty of Science. His contributions advance efficient data management and sensing technologies for embedded and IoT systems.