A method for controlling a temperature of a heating element can include: measuring a temperature of the heating element using a temperature sensor; estimating a temperature of the heating element based on a heat transfer model of the heating element; calculating a variation of the estimated temperature and a variation of the measured temperature; and determining whether a failure of the temperature sensor occurs based on the calculated variation of the estimated temperature and the calculated variation of the measured temperature.

A secure lockable enclosure having a compartment therein, includes an electronically-actuated latching mechanism coupled to a door; a network interface; a sensor for sensing a characteristic related to a user attempting to gain access to the compartment; an environmental controller for heating and/or cooling the compartment; and a processor. The processor being adapted to (i) cause the network interface to transmit information indicative of a sensed characteristic of a user attempting to gain access to the compartment and capable of processing an unlock signal, and (ii) control the environmental controller based on a characteristic of an item placed in the compartment. An exemplary method controlling access by a user to the enclosure includes the steps of receiving identification information of the user from sensors associated with the enclosure; receiving identification information of an account holder; verifying the received identification information of the user against the account holder information and providing an unlock code to the lock device if the identification information of the user and account holder matches.

A control system for an HVAC system having a plurality of HVAC components comprises a controller having a processor and a memory, the controller in signal communication with at least one of the plurality of HVAC components, the controller configured to: determine an aggregate demand of the HVAC system; determine an initial setpoint in response to the aggregate demand; determine a demand forecast in response to the aggregate demand; determine a setpoint offset in response to the demand forecast; generate an adaptive setpoint by combining the initial setpoint and the setpoint offset; and provide the adaptive setpoint to the at least one of the plurality of HVAC components.

Systems and methods for managing a programmable thermostat are described herein. One or more system embodiments include a programmable thermostat having a first management profile; a data acquisition subsystem; and a data analysis subsystem. The data acquisition subsystem is configured to receive thermostat data from the programmable thermostat, and the data analysis subsystem is configured to receive the thermostat data from the data acquisition subsystem, and determine a second management profile for the programmable thermostat based, at least in part, on the thermostat data.

A technique for energy sample forecasting of heating, venting and air conditioning-refrigeration (HVAC-R) systems is disclosed. In an example, a first expected energy sample of a HVAC-R system at a first time period is forecasted by modelling actual energy samples of the HVAC-R system at previous time periods using a statistically-based seasonal-autoregressive integrated moving average (SARIMA) model. Further, an anomaly is detected at the first time period when deviation between the first expected energy sample and an actual energy sample at the first time period is greater than a dynamic context sensitive threshold. Also, an expected energy sample at next time period is forecasted by modelling a second expected energy sample of the HVAC-R system at the first time period using the statistically-based SARIMA model upon detecting anomaly. The second expected energy sample is forecasted by modelling the actual energy samples at the previous time periods using a physical model.