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Control is and will continue to be a key discipline for realizing the objectives of smart grid initiatives. Research in control science and engineering is not limited to one or a few application concepts but is pervasive across the smart grid ecosystem. The principal contribution of this paper is to review, from a system-architectural perspective, how control enables smart grid applications. Application “templates” are presented for direct load control, automated demand response, microgrid optimization, control for distribution grids, wide-area control, and market-centric control. Technological developments, including in power electronics, that are enabling smart grid control research and applications are also itemized and two cross-cutting needs/opportunities for future research discussed. We conclude with a summary of a recent status report on the progress that has been made in the United States, noting also the challenges to further progress, in renewable generation, energy efficiency, and carbon reduction. [ABSTRACT FROM PUBLISHER]

The architecture, engineering, and construction (AEC) industry in the United States faces a scarcity of skilled labor workers. Previous efforts in academia and industry have investigated various approaches to improve worker productivity. Voice-based systems present opportunities to improve worker productivity, but their usability and applicability in unstructured and noisy occupational settings such as those inherent in construction projects has not been explored. This study describes a prototype Voice-based Intelligent Virtual Agent (VIVA) and evaluates its impact on construction worker productivity. A usability study was conducted involving 20 students to evaluate VIVA's support on workers' performance and cognitive workload. The results corroborated performance gains with VIVA. Results from workload demonstrates that intervention through voice assistance does not impose cognitive burden on workers. The proposed solution provides a novel use of voice-based agents, in a dynamic and noisy occupational setting, compared to the conventional use of voice assistants in stationary or structured settings. • Voice-Based methods have great potential to support construction worker's productivity. • The understanding of voice-based interactions in specific construction contexts is critical for technology effectiveness. • The authors developed and evaluated a Voice-based System based on IoT to support Worker's activities. • The developed system improved users' performance without negatively impactive perceived workload. [ABSTRACT FROM AUTHOR]

Traffic accidents are one of the leading causes of fatalities in the US. An important indicator of survival rates after an accident is the time between the accident and when emergency medical personnel are dispatched to the scene. Eliminating the time between when an accident occurs and when first responders are dispatched to the scene decreases mortality rates by 6%. One approach to eliminating the delay between accident occurrence and first responder dispatch is to use in-vehicle automatic accident detection and notification systems, which sense when traffic accidents occur and immediately notify emergency personnel. These in-vehicle systems, however, are not available in all cars and are expensive to retrofit for older vehicles. This paper describes how smartphones, such as the iPhone and Google Android platforms, can automatically detect traffic accidents using accelerometers and acoustic data, immediately notify a central emergency dispatch server after an accident, and provide situational awareness through photographs, GPS coordinates, VOIP communication channels, and accident data recording. This paper provides the following contributions to the study of detecting traffic accidents via smartphones: (1) we present a formal model for accident detection that combines sensors and context data, (2) we show how smartphone sensors, network connections, and web services can be used to provide situational awareness to first responders, and (3) we provide empirical results demonstrating the efficacy of different approaches employed by smartphone accident detection systems to prevent false positives. [ABSTRACT FROM AUTHOR]

Heating, ventilation, and air conditioning (HVAC) systems account for more than half of the residential energy consumption in the United States. Since most people do not have the expertise to control the HVAC system efficiently, unnecessary energy consumption is often caused by wasteful behaviors (overheating/overcooling and operation without occupancy). New Internet of Things (IoT) products for a smart home have the potential for energy saving by reducing the unnecessary operation of the energy system in a residential house. However, many people still hesitate to adopt this product with uncertain economic benefit. This work explores a co-simulation platform to assess energy saving impact and economic benefits of occupancy driven thermostat in a residential house. An occupancy simulator was devised and utilized to consider the random nature of the occupancy in a typical single family residential house. Six HVAC system control strategies were explored based on three types of thermostats (always on; schedule based; and occupancy driven) as well as two setpoint control algorithms (fixed setpoint; and adaptive control). Energy-plus was integrated into the co-simulation platform, which evaluated energy consumption and indoor temperature of a residential house in five climate conditions. User's comfort level was evaluated using the adaptive model for the six different control strategies in each location. The result showed that the occupancy information-based control algorithm can save about between 11% and 34% of energy without significantly risking the occupant's comfort level. The work also suggests that the adaptive control model has a more tangible saving impact as IoT products can easily integrate outside temperature. Depending on the locations, adaptive control can save up to 54% of energy consumption, and the occupancy information can add additional energy saving impact by 20%. Payback period varies for different control strategies and depends on the rate of utility as well as the amount of energy saving. Compared with the most wasteful control strategy (fixed setpoint - always on), adding a thermostat with adaptive – occupancy driven control strategy can lead to less than one year of payback period regardless of location. [ABSTRACT FROM AUTHOR]