A Framework for Energy-Efficiency in Smart Home Environments

Part 7: Cyber-Physical Systems

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

Atopy, home environment and the risk of childhood-onset type 1 diabetes: a population-based case-control study

Background: The marked increases in the incidence of type 1 diabetes in recent decades strongly suggest the role of environmental influences. These environmental influences remain largely unknown.

Adolescent ecstasy use and depression: cause and effect, or two outcomes of home environment?

Background: This study assessed the association between adolescent ecstasy use and depressive symptoms in adolescence. Methods: The Belfast Youth Development Study surveyed a cohort annually from age 11 to 16 years. Gender, Strengths and Difficulties Questionnaire emotional subscale, living arrangements, parental affluence, parent and peer attachment, tobacco, alcohol, cannabis and ecstasy use were investigated as predictors of Short Mood and Feelings Questionnaire (SMFQ) outcome. Results: Of 5371 respondents, 301 (5.6%) had an SMFQ > 15, and 1620 (30.2) had missing data for SMFQ. Around 8% of the cohort had used ecstasy by the end of follow-up. Of the non-drug users, ∼2% showed symptoms of depression, compared with 6% of those who had used alcohol, 6% of cannabis users, 6% of ecstasy users and 7% of frequent ecstasy users. Without adjustment, ecstasy users showed around a 4-fold increased odds of depressive symptoms compared with non-drug users [odds ratio (OR) = 0.26; 95% confidence interval (CI) = 0.10, 0.68]. Further adjustment for living arrangements, peer and parental attachment attenuated the association to under a 3-fold increase (OR = 0.37; 95% CI = 0.15, 0.94). There were no differences by frequency of use. Conclusions: Ecstasy use during adolescence may be associated with poorer mental health; however, this association can be explained by the confounding social influence of family dynamics. These findings could be used to aid effective evidence-based drug policies, which concentrate criminal justice and public health resources on reducing harm.

Temperament test for re-homed dogs validated through direct behavioral observation in shelter and home environment

This study was the first attempt to carry out a validation of a temperament test (TT) for shelter dogs that addressed the topics of inter- and intra-raters agreements, test-retest reliability, and validity. The TT consisted of 22 subtests. Each dog was approached and handled by an unfamiliar person and made to interact with a same- and an opposite-gender conspecific. Dogs were tested twice in the shelter and once in their new homes 4 months after adoption to evaluate consistency in behavioral assessment. Playfulness, trainability, problem solving abilities, food possessiveness, and reactivity to sudden stimuli were also evaluated. Testers scored dogs' responses in terms of confidence, fearfulness, and aggressiveness. Results highlighted strengths and limits of this TT that was devised to help shelter staff in matching dogs' personality and owners' expectations. Methodological constraints when working with sheltered dogs are unavoidable; however, the test proved to be overall feasible, reliable, and valid although further studies are needed to address the critical issues that emerged. © 2011 Elsevier Inc.

A Designer’s Approach: Exploring how Autistic Adults with Additional Learning Disabilities Experience their Home Environment

Autistic adults with limited speech and additional learning disabilities are people whose perceptions and interactions with their environment are unique, but whose experiences are under-explored in design research. This PhD by Practice investigates how people with autism experience their home environment through a collaboration with the autism charity Kingwood Trust, which gave the designer extensive access to a community of autistic adults that it supports. The PhD reflects upon a neurotypical designer’s approach to working with autistic adults to investigate their relationship with the environment. It identifies and develops collaborative design tools for autistic adults, their support staff and family members to be involved. The PhD presents three design studies that explore a person’s interaction with three environmental contexts of the home i.e. garden, everyday objects and interiors. A strengths-based rather than a deficit-based approach is adopted which draws upon an autistic person’s sensory preferences, special interests and action capabilities, to unravel what discomfort and delight might mean for an autistic person; this approach is translated into three design solutions to enhance their experience at home. By working beyond the boundaries of a neurotypical culture, the PhD bridges the autistic and neurotypical worlds of experience and draws upon what the mainstream design field can learn from designing with autistic people with additional learning disabilities. It also provides insights into the subjective experiences of people who have very different ways of seeing, doing and being in the environment

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.