DALI LED Driver Control System for Lighting Operations Based on Raspberry Pi and Kernel Modules

Unsupervised Clustering Pipeline to Obtain Diversified Light Spectra for Subject Studies and Correlation Analyses

Current subject studies and data-driven approaches in lighting research often use manually selected light spectra, which usually exhibit a large bias due to the applied selection criteria. This paper, therefore, presents a novel approach to minimize this bias by using a data-driven framework for selecting the most diverse candidates from a given larger set of possible light spectra. The spectral information per wavelength is first reduced by applying a convolutional autoencoder. The relevant features are then selected based on Laplacian Scores and transformed to a two-dimensional embedded space for subsequent clustering. The low dimensional embedding, from which the required diversity follows, is done with respect to the locality of the features. In a second step, photometric parameters are considered and a second clustering is performed. As a result of this algorithmic pipeline, the most diverse selection of light spectra complying with a given set of relevant photometric parameters can be extracted and used for further experiments or applications.

Real-Time Performance and Response Latency Measurements of Linux Kernels on Single-Board Computers

This research performs real-time measurements of Linux kernels with real-time support provided by the PREEMPT_RT patch on embedded development devices such as BeagleBoard and Raspberry Pi. The experimental measurements of the Linux real-time performance on these devices are based on real-time software modules developed specifically for the purposes of this research. Taking in consideration the constraints of the specific hardware platforms under investigation, new measurements software was developed. The measurement algorithms are designed upon response and periodic task models. Measurements investigate latencies of real-time applications at user and kernel space. An outcome of this research is that the proposed performance measurements approach and evaluation methodology could be applied and deployed on other Linux-based boards and platforms. Furthermore, the results demonstrate that the PREEMPT_RT patch overall improves the Linux kernel real-time performance compared to the standard one. The reduced worst-case latencies on such devices running Linux with real-time support could make them potentially more suitable for real-time applications as long as a latency value of about 160 μs, as an upper bound, is an acceptable safety margin.

A Novel Smart Energy Management as a Service over a Cloud Computing Platform for Nanogrid Appliances

There will be a dearth of electrical energy in the world in the future due to exponential increase in electrical energy demand of rapidly growing world population. With the development of Internet of Things (IoT), more smart appliances will be integrated into homes in smart cities that actively participate in the electricity market by demand response programs to efficiently manage energy in order to meet this increasing energy demand. Thus, with this incitement, the energy management strategy using a price-based demand response program is developed for IoT-enabled residential buildings. We propose a new EMS for smart homes for IoT-enabled residential building smart devices by scheduling to minimize cost of electricity, alleviate peak-to-average ratio, correct power factor, automatic protective appliances, and maximize user comfort. In this method, every home appliance is interfaced with an IoT entity (a data acquisition module) with a specific IP address, which results in a wide wireless system of devices. There are two components of the proposed system: software and hardware. The hardware is composed of a base station unit (BSU) and many terminal units (TUs). The software comprises Wi-Fi network programming as well as system protocol. In this study, a message queue telemetry transportation (MQTT) broker was installed on the boards of BSU and TU. In this paper, we present a low-cost platform for the monitoring and helping decision making about different areas in a neighboring community for efficient management and maintenance, using information and communication technologies. The findings of the experiments demonstrated the feasibility and viability of the proposed method for energy management in various modes. The proposed method increases effective energy utilization, which in turn increases the sustainability of IoT-enabled homes in smart cities. The proposed strategy automatically responds to power factor correction, to protective home appliances, and to price-based demand response programs to combat the major problem of the demand response programs, which is the limitation of consumer’s knowledge to respond upon receiving demand response signals. The schedule controller proposed in this paper achieved an energy saving of 6.347 kWh real power per day, this paper achieved saving 7.282 kWh apparent power per day, and the proposed algorithm in our paper saved $2.3228388 per day.

DALI Bridge FPGA-Based Implementation in a Wireless Sensor Node for IoT Street Lighting Applications

Smart lighting systems based on the Digital Addressable Lighting Interface (DALI) protocol are the most suitable for street lighting systems, allowing digital lighting control operations. Unfortunately, the microcontrollers, which are commonly used in the Wireless Sensor Network nodes to control the lamps, do not implement this protocol. The DALI protocol implemented by software in the microcontroller consumes hardware resources (timers), processing time and requires a precise temporal analysis of the application, due to the strict bit times and the Manchester coding that it uses. In this work, the design of a bridge is proposed to free the microcontroller from the implementation of the DALI protocol. The novelty of this work is the implementation of the DALI Bridge in a low-cost Field-Programmable Gate Array (FPGA) with low power consumption. The bridge has been described in the hardware description language following the 1076-93 and 1076.3-97 standards, to guarantee its portability. The results of the synthesis show that a minimum amount of logical and routing resources is used, that the power consumption is in the order of tens of mW, that it has a very small latency time and that it supports a high operating frequency, which allows adding new functions. Its operation is verified by implementing a wireless sensor node using an FPGA of the Lattice Semiconductor iCE40 family.

COTS-Based Architectural Framework for Reliable Real-Time Control Applications in Manufacturing

The challenge of keeping the development and implementation of real-time control systems reliable and efficient and at the same time, low-cost and low-energy, is getting harder. This is because system designers and developers are faced with the dependability, inflexibility and often high-cost of specialized or custom-built hardware and software components. This research attempts to tackle issues such as the reliability and efficiency of real-time control systems and advance further the current state-of-the-art. For this purpose, a strong emphasis is placed on finding novel efficient solutions based on standardized and commercially available off-the-shelf hardware/software components. In this direction, this research applies credible and feasible methodologies (e.g., model-based design, component-based design, formal verification, real-time scheduling, prototyping, and validation) in an innovative enhanced way. As an important outcome, a versatile integrative design approach and architectural framework (VIDAF) is proposed, which supports the development and implementation of reliable real-time control systems and applications using commercial off-the-shelf (COTS) components. The feasibility and applicability of the proposed system’s architecture are evaluated and validated through a system application in embedded real-time control in manufacturing. The research outcomes are expected to have a positive impact on emerging areas such as the Industrial Internet of Things (IIoT).