Many user studies of home automation, as the most familiar representative of the Internet of Things, have shown the difficulty of developing technology that users understand and like. It helps to state requirements as largely-independent features, but features are not truly independent, so this incurs the cost of managing and explaining feature interactions. We propose to compose features at runtime, resolving their interactions by means of priority. Although the basic idea is simple, its details must be designed to make users comfortable by balancing manual and automatic control. On the technical side, its details must be designed to allow meaningful separation of features and maximum generality. As evidence that our composition mechanism achieves its goals, we present three substantive examples of home automation, and the results of a user study to investigate comprehension of feature interactions. A survey of related work shows that this proposal occupies a sensible place in a design space whose dimensions include actuator type, detection versus resolution strategies, and modularity.
It is also possible to view home automation in terms of high-level actions that must be completed over time @cite_5 . In the remainder of this section, however, we turn to the more typical approach to the Internet of Things, in which actuators can change settings at any time (as described in ).
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Networked devices such as locks and thermostats are now cheaply available, which is accelerating the adoption of home automation. But unintended behaviors of programs that control automated homes can pose severe problems, including security risks (e.g., accidental disarming of alarms). We facilitate predictable control of automated homes by letting users “fast forward” their program and observe its possible future behaviors under different sequences of inputs and environmental conditions. A key challenge that we face, which is not addressed by existing program exploration techniques, is to systematically handle time because home automation programs depend intimately on absolute and relative timing of inputs. We develop an approach that models programs as timed automata and incorporates novel mechanisms to enable scalable and comprehensive exploration of their behavior. We implement our approach in a tool called DeLorean and apply it to 10 real home automation programs. We find that it can fast forward these programs 3.6 times to 36K times faster than real time and uncover unintended behaviors in them. Abstract In this paper, a coordination approach for thermostat-controlled household appliances is developed. Under consideration are heating and cooling devices such as refrigerators, freezers, water boilers and heat pumps, which are usually characterized by an intermittent (duty cycle) operation. Without influence from the outside, an internal hysteresis switching controller toggles the “on off” state of a device when its temperature boundary is reached. In order to realize the approach proposed here, the devices are connected to a central control entity by two-way communication. The coordination consists of a step-wise heuristic solution of a binary optimization problem, which serves to select a number of devices in each time step that are subject to compulsory switching, i.e. toggling the “on off” state. It allows a large group of devices to track a setpoint trajectory with its aggregated power consumption, acting like a distributed virtual energy storage, while the individual temperature bounds of the appliances are not violated. This behavior can be used for grid-control purposes, such as the provision of active power reserves. It will be shown that the group of appliances can be characterized by an approximate aggregated dynamical model consisting of a first-order differential equation together with an approximate aggregated nonlinear cost function penalizing the control actions. The developed methodology is evaluated in a numerical simulation with a small appliance cluster corresponding to a residential housing area. As robots begin to enter our homes and workplaces, they will have to deal with the devices and appliances that are already there. Unfortunately, devices that are easy for humans to operate often cause problems for robots [3]. In teleoperation settings, the lack of tactile feedback often makes manipulation of buttons and switches awkward and clumsy [7]. Also, the robot's gripper often occludes the control, making teleoperation difficult. In the autonomous setting, perception of small buttons and switches is often difficult due to sensor limitations and poor lighting conditions. Adding depth information does not help much, since many of the controls we want to manipulate are small, and often close to the noise threshold of currently-available depth sensors typically installed on a mobile robot. This makes it extremely difficult to segment the controls from the other parts of the device. In this paper, we present a shared autonomy approach to the operation of physical device controls. A human operator gives high-level guidance, helps identify controls and their locations, and sequences the actions of the robot. Autonomous software on our robot performs the lower-level actions that require closed-loop control, and estimates the exact positions and parameters of controls. We describe the overall system, and then give the results of our initial evaluations, which suggest that the system is effective in operating the controls on a physical device. Nowadays, we can no longer imagine that Internet can be considered just a network of computers. We also have to state that it's becoming even more a network of things. With this in mind, this paper introduces a long range Internet connected robot teleoperation system based on Internet of Things (IoT). The aim is to support operators during remote teleoperation of robotic systems in situations in which the remote control devices loose the connection with the on-board receivers. This situation can occur either due to the lost of the line-of-sight or due to possible damages of the devices. IoT allows to connect remote and mobile things or machines. It also assets through the use of wireless communications and low-cost sensors, computing and storage devices. Approaches based on IoT have been already applied in traffic monitoring, smart homes, smart parking management, vehicle tracking system and other industrial applications. We used the system to control a mobile robot without range barriers provided that the robot and the remote control device must be connected to the Internet.