Provided is a setting method of a Wi-Fi doorbell (2), in which a Wi-Fi doorbell (2) comprising a camera capable of reading a two-dimensional code and a mobile communication terminal (4) comprising a display unit (6) capable of displaying the two-dimensional code are used. The setting method comprises steps of causing the display unit (6) to display a two-dimensional code in which password information for enabling the Wi-Fi doorbell (2) to connect to a network (5) via a Wi-Fi router (20) is embedded reading the two-dimensional code by the camera (9) of the Wi-Fi doorbell (2); and setting the Wi-Fi doorbell (2) to a state where the Wi-Fi doorbell (2) can perform communication with a remotely disposed server (3) via the Wi-Fi router (20), based on the read two-dimensional code.

An assembly and method for using weather sensors with enhanced modular capability is disclosed. The weather sensor assembly generally comprises a cap module, middle module, and a base module, where the cap module, middle module(s) and the base module are stacked adjacently to provide environmental sealing, weather sensing, and electrical connectivity to the weather sensor assembly. One or more ring mechanisms may be included that interlock the cap module, middle module(s), base module to form the weather sensor assembly into an integrated unit. Moreover, the ring mechanisms enable further modules to be added to the weather sensor assembly for additional capabilities. By doing so, each of the modules in the weather sensor assembly may be independent units that can be removed, reordered, swapped, and added for desired sensing modalities and environments.

An assembly and method for using weather sensors with enhanced modular capability is disclosed. The weather sensor assembly generally comprises a cap module, middle module, and a base module, where the cap module, middle module(s) and the base module are stacked adjacently to provide environmental sealing, weather sensing, and electrical connectivity to the weather sensor assembly. One or more ring mechanisms may be included that interlock the cap module, middle module(s), base module to form the weather sensor assembly into an integrated unit. Moreover, the ring mechanisms enable further modules to be added to the weather sensor assembly for additional capabilities. By doing so, each of the modules in the weather sensor assembly may be independent units that can be removed, reordered, swapped, and added for desired sensing modalities and environments.

The present disclosure describes various systems and methods for measuring environmental parameters. In one embodiment, such as system comprises a pole that is equipped with various instruments (sensors) at various heights along the length of the pole. With such an instrumented pole, a local vertical profile of parameters that relate to wind conditions and air quality can be obtained. These parameters can include one or more of wind speed and direction, air turbulence, air temperature and humidity, concentrations of pollutant gases within the air, and concentrations of pollutant particles within the air. In some embodiments, the system can further measure other parameters that are relevant to the migration of the air and, therefore, the pollutants it contains.

The present disclosure describes various systems and methods for measuring environmental parameters. In one embodiment, such as system comprises a pole that is equipped with various instruments (sensors) at various heights along the length of the pole. With such an instrumented pole, a local vertical profile of parameters that relate to wind conditions and air quality can be obtained. These parameters can include one or more of wind speed and direction, air turbulence, air temperature and humidity, concentrations of pollutant gases within the air, and concentrations of pollutant particles within the air. In some embodiments, the system can further measure other parameters that are relevant to the migration of the air and, therefore, the pollutants it contains.

An electronic device includes one or more processors and memory storing a first logical table for a first time. The first logical table includes a plurality of logical columns, each logical column including an input vector of a plurality of input parameters corresponding to a respective time, and a plurality of logical rows intersecting with the plurality of logical columns, each logical row corresponding to a respective input parameter. The device updates a respective logical column with a first input vector that corresponds to a second time subsequent to the first time, thereby obtaining a second logical table; obtains a first transposed kernel matrix between the second logical table for the second time and the first input vector; determines a first predicted output value for the second time; and outputs the first predicted output value.

This disclosure generally relates to a light electric vehicle. More specifically, this disclosure describes how to limit or restrict access to a light electric vehicle based on determined or anticipated environmental conditions. The disclosure also describes how to change one or more capabilities or operating parameters of the light electric vehicle based on determined and/or anticipated environmental conditions.

The invention relates to training a machine learning algorithm and predicting a value for a weather data variable, preferably at a field or sub-field level. In this respect, according to the invention, a method for predicting a value for at least one weather data variable for at least one instant of time in the future, is provided, the method comprising the following method steps: feeding a machine learning algorithm with a predicted weather dataset that comprises at least one predicted value for the said at least one weather data variable for the said at least one instant of time in the future and for at least one grid point of a first grid covering at least a part of the Earth's surface, feeding the machine learning algorithm with an observed environmental dataset that comprises at least one ground truth value for at least one environmental data variable for at least one grid point of a second grid covering at least the said part of the Earth's surface, and outputting by the machine learning algorithm a predicted value for the said at least one weather data variable for the said at least one instant of time in the future. In this way, a possibility for field specific weather predictions for providing field zone specific treatment recommendations at a small-meshed grid level may be provided.

This disclosure relates to precision agriculture that relies on monitoring micro-climatic conditions of a farm to make accurate disease forecasts for better crop protection and improve yield efficiency. Conventional systems face challenge in managing energy and bandwidth of transmission considering the humongous volume of data generated in a field through IoT based sensors. The present disclosure provides energy-efficient adaptive parameter sampling from the field by optimally configuring the parameter sampling rate thereby maximizing energy-efficiency. This helps reduce unnecessary traffic to a cloud while extending network lifetime.

Systems and methods for enabling consistent smooth takeoffs and landings of vertical and/or short-runway takeoff and landing aircraft at sites with gusty conditions. The system includes a network of wind measurement stations deployed around the perimeter of a takeoff/landing site for spatio-temporally characterizing wind fluctuations (e.g., wind gusts) that enter a volume of airspace overlying the site, data processing means for deriving information about the fluctuations from the wind measurements, communication means for transmitting disturbance information to the aircraft, and a flight control system onboard the aircraft that is configured to use the disturbance information to control the aircraft in a manner that compensates for the fluctuations. The wind measurement units may include laser Doppler anemometers, sound detection and ranging systems or other devices capable of simultaneous spatially and temporally resolved wind measurements.