Evaluating the More Suitable ISM Frequency Band for IoT-Based Smart Grids: A Quantitative Study of 915 MHz vs. 2400 MHz

Abstract

IoT has begun to be employed pervasively in industrial environments and critical infrastructures thanks to its positive impact on performance and efficiency. Among these environments, the Smart Grid (SG) excels as the perfect host for this technology, mainly due to its potential to become the motor of the rest of electrically-dependent infrastructures. To make this SG-oriented IoT cost-effective, most deployments employ unlicensed ISM bands, specifically the 2400 MHz one, due to its extended communication bandwidth in comparison with lower bands. This band has been extensively used for years by Wireless Sensor Networks (WSN) and Mobile Ad-hoc Networks (MANET), from which the IoT technologically inherits. However, this work questions and evaluates the suitability of such a “default” communication band in SG environments, compared with the 915 MHz ISM band. A comprehensive quantitative comparison of these bands has been accomplished in terms of: power consumption, average network delay, and packet reception rate. To allow such a study, a dual-band propagation model specifically designed for the SG has been derived, tested, and incorporated into the well-known TOSSIM simulator. Simulation results reveal that only in the absence of other 2400 MHz interfering devices (such as WiFi or Bluetooth) or in small networks, is the 2400 MHz band the best option. In any other case, SG-oriented IoT quantitatively perform better if operating in the 915 MHz band.

Performance optimization of LoRa nodes for the future smart city/industry

“…The energy consumption rate (i.e., power consumption), expressed in Watts, can be computed as the energy consumed per sensing cycle divided by the time duration of 2 Although there is a technique called channel activity detection, it is geared towards detecting the preamble of potentially colliding LoRa transmissions. Therefore, when a transmission-whose preamble has already been sent-is on the air, there is no guarantee that it could be detected by other neighboring LoRa nodes.…”

Performance measurements of communication access technologies and improved cognitive radio model for smart grid communication

“…This is due to the varying propagation conditions in an SG environment. However, the Log‐Normal shadowing path loss model has been the most widely employed in SGs and in Internet of Things (IoT)‐based SG . Hence, the Log‐Normal shadowing path loss ( LNP L ) can be expressed as where P L ( d 0) is the path loss initially present due to a reference distance ( d 0) of 1 m; n is the path loss exponent that varies with the environmental conditions and adjusts the rate at which the power degrades with distance, and d is the entire covered distance of propagation path.…”

“…However, the Log-Normal shadowing path loss model has been the most widely employed in SGs and in Internet of Things (IoT)-based SG. [48][49][50] Hence, the Log-Normal shadowing path loss (LNP L ) can be expressed as…”

The Development and Field Evaluation of an IoT System of Low-Power Vibration for Bridge Health Monitoring

“…Manual monitoring has obvious shortcomings: (1) Monitoring is typically not regular and some results are obtained by empirical estimation; (2) due to the limitation of data collection frequency, testing results often lag behind the damage of the bridge [ 7 ], and there are no early warnings of damage; (3) due to the lack of real-time monitored data, it is difficult to understand the development of damage. With the advance of the Internet of Things (the IoT), health monitoring of infrastructure has an opportunity for technological advances [ 8 , 9 ]. By making use of IoT, better interconnection among all infrastructure objects can be established to enhance data collection, transmission and processing.…”