Smart energy meter based on a long-range wide-area network for a stand-alone photovoltaic system

Long-range wide-area network (LoRaWAN) has emerged as a key technology for Internet of Things (IoT) applications worldwide owing to its cost-effectiveness, robustness to interference, low power, licensed-free frequency band, and long-range connectivity, thanks to the adaptive data rate. In this contribution, an IoT-enabled smart energy meter based on LoRaWAN technology (SEM-LoRaWAN) is developed to measure the energy consumption for a photovoltaic (PV) system and send real-time data to the utility/consumers over the Internet for billing/monitoring purposes. The proposed SEM-LoRaWAN is implemented in a PV system to monitor related parameters (i.e., voltage, current, power, energy, light intensity, temperature, and humidity) and update this information to the cloud. A LoRa shield is attached to an Arduino microcontroller with several sensors to gather the required information and send it to a LoRaWAN gateway. We also propose an algorithm to compose data from multiple sensors as payloads and upload these data using the gateway to The Things Network (TTN). The AllThingsTalkMaker IoT server is integrated into the TTN to be accessed using Web/mobile application interfaces. System-level tests are conducted using a fabricated testbed and connected to a solar panel to prove the SEM-LoRaWAN effectiveness in terms of functionality, simplicity, reliability, and cost. The connectivity between the system and users is achieved using smartphones/laptops. Results demonstrate a smooth system operation with detailed and accurate measurements of electrical usage and PV environmental conditions in real-time

Smart energy meter based on a long-range wide-area network for a stand-alone photovoltaic system

Long-range wide-area network (LoRaWAN) has emerged as a key technology for Internet of Things (IoT) applications worldwide owing to its cost-effectiveness, robustness to interference, low power, licensed-free frequency band, and long-range connectivity, thanks to the adaptive data rate. In this contribution, an IoT-enabled smart energy meter based on LoRaWAN technology (SEM-LoRaWAN) is developed to measure the energy consumption for a photovoltaic (PV) system and send real-time data to the utility/consumers over the Internet for billing/monitoring purposes. The proposed SEM-LoRaWAN is implemented in a PV system to monitor related parameters (i.e., voltage, current, power, energy, light intensity, temperature, and humidity) and update this information to the cloud. A LoRa shield is attached to an Arduino microcontroller with several sensors to gather the required information and send it to a LoRaWAN gateway. We also propose an algorithm to compose data from multiple sensors as payloads and upload these data using the gateway to The Things Network (TTN). The AllThingsTalkMaker IoT server is integrated into the TTN to be accessed using Web/mobile application interfaces. System-level tests are conducted using a fabricated testbed and connected to a solar panel to prove the SEM-LoRaWAN effectiveness in terms of functionality, simplicity, reliability, and cost. The connectivity between the system and users is achieved using smartphones/laptops. Results demonstrate a smooth system operation with detailed and accurate measurements of electrical usage and PV environmental conditions in real-time

Cardiopulmonary resuscitation interruptions with use of a load-distributing band device during emergency department cardiac arrest

10.1016/j.annemergmed.2010.01.004Annals of Emergency Medicine563233-241AEME

Improved neurologically intact survival with the use of an automated, load-distributing band chest compression device for cardiac arrest presenting to the emergency department

10.1186/cc11456Critical Care164R14

Efficient developmental mis-targeting by the sporamin NTPP vacuolar signal to plastids in young leaves of sugarcane and Arabidopsis

Plant vacuoles are multi-functional, developmentally varied and can occupy up to 90% of plant cells. The N-terminal propeptide (NTPP) of sweet potato sporamin and the C-terminal propeptide (CTPP) of tobacco chitinase have been developed as models to target some heterologous proteins to vacuoles but so far tested on only a few plant species, vacuole types and payload proteins. Most studies have focused on lytic and protein-storage vacuoles, which may differ substantially from the sugar-storage vacuoles in crops like sugarcane. Our results extend the evidence that NTPP of sporamin can direct heterologous proteins to vacuoles in diverse plant species and indicate that sugarcane sucrose-storage vacuoles (like the lytic vacuoles in other plant species) are hostile to heterologous proteins. A low level of cytosolic NTPP-GFP (green fluorescent protein) was detectable in most cell types in sugarcane and Arabidopsis, but only Arabidopsis mature leaf mesophyll cells accumulated NTPP-GFP to detectable levels in vacuoles. Unexpectedly, efficient developmental mis-trafficking of NTPP-GFP to chloroplasts was found in young leaf mesophyll cells of both species. Vacuolar targeting by tobacco chitinase CTPP was inefficient in sugarcane, leaving substantial cytoplasmic activity of rat lysosomal beta-glucuronidase (GUS) [ER (endoplasmic reticulum)-RGUS-CTPP]. Sporamin NTPP is a promising targeting signal for studies of vacuolar function and for metabolic engineering. Such applications must take account of the efficient developmental mis-targeting by the signal and the instability of most introduced proteins, even in storage vacuoles