Many technical communities are vigorously pursuing research topics that contribute to the Internet of Things (IoT). Nowadays, as sensing, actuation, communication, and control become even more sophisticated and ubiquitous, there is a significant overlap in these communities, sometimes from slightly different perspectives. More cooperation between communities is encouraged. To provide a basis for discussing open research problems in IoT, a vision for how IoT could change the world in the distant future is first presented. Then, eight key research topics are enumerated and research problems within these topics are discussed.

/pdf/research-directions-for-the-internet-of-things-2x8dpg1w6r.pdf

Research Directions for the Internet of Things

The Internet of Things vision: Key features, applications and open issues

https://pure.rug.nl/ws/files/2357318/2013EnergyBuildingsNguyen.pdf

Energy intelligent buildings based on user activity: A survey

A thermostat for controlling an HVAC system is described, the thermostat having a user interface that is visually pleasing, approachable, and easy to use while also providing ready access to, and intuitive navigation within, a menuing system capable of receiving a variety of different types of user settings and/or control parameters. For some embodiments, the thermostat comprises a housing, a ring-shaped user-interface component configured to track a rotational input motion of a user, a processing system configured to identify a setpoint temperature value based on the tracked rotational input motion, and an electronic display coupled to the processing system. An interactive thermostat menuing system is accessible to the user by an inward pressing of the ring-shaped user interface component. User navigation within the interactive thermostat menuing system is achievable by virtue of respective rotational input motions and inward pressings of the ring-shaped user interface component.

Thermostat user interface

Home heating is a major factor in worldwide energy use. Our system, PreHeat, aims to more efficiently heat homes by using occupancy sensing and occupancy prediction to automatically control home heating. We deployed PreHeat in five homes, three in the US and two in the UK. In UK homes, we controlled heating on a per-room basis to enable further energy savings. We compared PreHeat's prediction algorithm with a static program over an average 61 days per house, alternating days between these conditions, and measuring actual gas consumption and occupancy. In UK homes PreHeat both saved gas and reduced MissTime (the time that the house was occupied but not warm). In US homes, PreHeat decreased MissTime by a factor of 6-12, while consuming a similar amount of gas. In summary, PreHeat enables more efficient heating while removing the need for users to program thermostat schedules.

/pdf/preheat-controlling-home-heating-using-occupancy-prediction-4h2c9lm8ff.pdf

PreHeat: controlling home heating using occupancy prediction

Heating, ventilation and cooling (HVAC) is the largest source of residential energy consumption. In this paper, we demonstrate how to use cheap and simple sensing technology to automatically sense occupancy and sleep patterns in a home, and how to use these patterns to save energy by automatically turning off the home's HVAC system. We call this approach the smart thermostat. We evaluate this approach by deploying sensors in 8 homes and comparing the expected energy usage of our algorithm against existing approaches. We demonstrate that our approach will achieve a 28% energy saving on average, at a cost of approximately $25 in sensors. In comparison, a commercially-available baseline approach that uses similar sensors saves only 6.8% energy on average, and actually increases energy consumption in 4 of the 8 households.

/pdf/the-smart-thermostat-using-occupancy-sensors-to-save-energy-20hwucrj0i.pdf

The smart thermostat: using occupancy sensors to save energy in homes

Heating, ventilation, and cooling (HVAC) accounts for 38% of building energy usage, and over 15% of all US energy usage, making it one of the nation's largest energy consumers. Many attempts have been made to optimize the control of HVAC systems by minimizing the energy wasted in conditioning buildings that are unoccupied. Systems have been proposed that turn off HVAC systems when a house is unoccupied, or put the system into an energy saving deep-setback mode when the occupants are asleep. An area that has not been as well explored is the retrofitting of centralized HVAC systems to save energy when the residents are at home and awake. In this paper, we demonstrate how to use cheap, off-the-shelf sensors and actuators to retrofit a centralized HVAC system and enable rooms to be heated or cooled individually, in order to reduce waste caused by conditioning unoccupied rooms. We call this approach room-level zoning. Sensors are used to detect occupancy in rooms which allows the learning of occupancy patterns and prediction of room occupancy. Unoccupied rooms can be allowed to drift away from a user defined comfortable temperature if they are less likely to be used in the near future while occupied rooms are maintained at a comfortable temperature. We implement room-level zoning in a 1400 square foot house by retrofitting an existing centralized HVAC system with wireless temperature sensors to monitor room-level temperature, motion sensors to monitor occupancy, and wirelessly actuatable dampers to control the flow of conditioned air through the house. Initial analysis indicates that this method has a 20.5% energy savings over the existing single-zoned thermostat.

Feasibility of retrofitting centralized HVAC systems for room-level zoning

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The smart thermostat: using occupancy sensors to save energy in homes

Feasibility of retrofitting centralized HVAC systems for room-level zoning

Feasibility of retrofitting centralized HVAC systems for room-level zoning