Technologies developed at universities are direct means to conceive a teaching plan for promoting science, technology, engineering and mathematics (STEM) at the K-12 level of education. This work-in-progress develops this notion: We elaborate a teaching plan for K-12 students based on technologies for recording plant bioelectrical activity. The teaching plan sketches hands-on activities, where pupils can self-assemble the electronic components such as the electro-potential sensor, analog-to-digital (ADC) converter, and Arduino board for processing, as designed by research students at Politecnico di Milano. Using our project as a blueprint, we aim to support other educators at universities to promote further STEM and expose pupils to technical developments at universities.

Promoting science, technology, engineering and mathematics (STEM) education at K-12 level motivates pupils to pursue technical careers at universities, which is of high importance due to skilled labor shortage and other factors. In particular, in Germany the population with a tertiary education level is less than the average in the European Union (35–41 %. Motivating the study of technical careers, this paper features a model for promoting STEM at the K-12 education level by developing joint teaching platforms with students at technical universities. The model is derived from hands-on experience at TU Berlin targeting a climate change topic: As part of student semester projects, Bachelor students integrated a humidity sensor into a drone and conducted atmospheric measurements. The resulting hard and software components provided by the students allowed the preparation of a lesson plan to promote STEM at the K-12 level. In this way, we synergically connect the means from the university with hands-on activities as means to promote STEM topics with K-12 students. The resulting benefits are manifold; students at the university develop technical skills and become part of a social intention to promote STEM topics on the one hand. On the second hand, pre-university students might have first-hand experiences with hardware prototypes and their applicability to relevant topics like climate change surveillance. The developed model may illustrate straightforward means for educators to design lesson plans, including actual practices at university and pre-university levels.

Accurate assessment of the state of charge (SoC) and state of health (SoH) of batteries provides critical information for effective operation in various battery applications. Such information optimizes charging, discharging, fault isolation, and maintenance decisions. Conventional techniques have shortcomings, including accuracy, cost, speed, and invasiveness. Recent research has introduced novel techniques, many exploiting magnetic field changes that occur during battery operation. This literature review summarizes conventional and novel measurement methodologies, highlighting any limitations of each. While magnetic field and X-ray approaches can overcome many of the shortcomings of conventional methods, further research is necessary to reduce costs, enhance safety, and enable real-time monitoring. The development of accurate, quick, and cost-effective measurement techniques will accelerate the integration of batteries into a rapidly increasing range of applications, including battery energy storage systems for behind the meter in buildings, facilitating electrification goals and the expansion of renewable energy.

What are recent topics in engineering education research addressed by the German scientific community? What are current trends, loose ends, and open directions? Is the research conducted locally or in networks across institutions? Following these questions, we aim to seize the German research community's trends, research directions, and contexts. We survey a systematic literature review covering publications of German researchers published in education-related conferences and jour-nals affiliated to IEEE between 2019 and 2022, resulting in 205 contributions in total. We analyze these works and illustrate results as contributions per topic, authors per institution, and the cross-work between institutions. The most prevalent topics turned out to be educational research, followed by curriculum design and remote instruction. Distinguishable, the German community also rehearse research for the K-12 level and develop Gamification techniques with the 18 % of contributions. Furthermore, we observe teams of three authors per contribution on average, and approximately 15 % of contributions are in collaboration among different institutions. On the basis of the literature review, we additionally provide our in-depth viewpoint discussing potential directions for German researchers and open a debate for best practices in supporting research on educational topics. We elaborate on effective means for promoting educational research in the community, more accessibility to learning technologies, and promotion of cross-work among institutions for further steeping the teaching research community within the IEEE.

IEEE11073 SDC is a fast growing standard, which offers a lot of new oportunites for medical device manufacturers and their customers. The goal of this Standard is to decrease the workload for nurses and doctors and increase the patients wellbeing by automation and interconnectivity of medical devices. To ensure that the communication between SDC devices work correctly, even under big load and other special conditions, there is the need to test theses devices. In order to test these devices in different communication scenarios, a testing environment and testing tools in form of Hardware-in-the-loop(HIL) are needed. This Paper investigates a method of testing SDCdevices in different communications scenarios through a concept for a testing software and a prototype.

LogicCircuits is a tool for direct or flipped-classroom teaching, and even self-study of digital circuits in computer engineering. It is HTML5-based and thus runs on all current platforms and operating systems in a browser. Its features include simple logic gates, combinatorial and sequential logic circuits, 4-valued logic, a VHDL-export of modeled circuits, and automatic generation of exam tasks that can be solved at home.

In this paper an indoor detection system is described that is able to detect persons in emergency situations such as fires and is robust even if some sensors fail. Actual occupancy values are measured by data fusion and bias correction algorithms, and extended with credibility values of the sensor measurements. Based on this credibility value of sensor nodes, a metaheuristic estimates plausible "occupancy estimations" of the building. If sensor telemetry is invalid or implausible, credibility is degraded, otherwise raised, letting the system dynamically react to defect devices. The sensor network is designed openly, making it easy to integrate new, previously unknown, sensors to the mesh. To validate the result, disaster scenarios were tested in a simulated public building environment.

This paper introduces an automated robust indoor detection system that is able to detect persons in emergency situations. Other than comparable projects, occupancy levels are not only measured by data fusion and bias correction algorithms, but also extended with sensor credibility. Based on trustworthiness of sensor nodes, a metaheuristic estimates plausible occupancy estimations of the building. According on whether sensor telemetry is valid and plausible, trust is degraded or raised, letting the system react to defect devices and occurring calamities. In addition, its sensor network is designed openly, making it easy to integrate new, previously unknown, sensors to the mesh. A sample web-based frontend is presented, which can be used to easily view, simulate and manipulate the algorithm. To validate the result, disaster scenarios were tested in a simulated public building environment.

The security of embedded devices is very important today because critical infrastructures like medical devices, transportation, communication, and smart grids deploy them in large numbers. In all of these areas cybersecurity is the enabler for safety as failing or compromised devices threaten the life of people. Often, it is not feasible securing already deployed devices because of high costs, missing physical access, or defective hardware. Therefore, the next generation devices deployed in the future have to be more secure and more resilient to cyber attacks.This paper proposes a new approach to secure these next generation devices by using program optimized Application Specific Processors (ASPs) and employing an easy to integrate development flow for embedded developers. It evaluates the security improvement by analyzing the vulnerability of the approach against typical attack patterns.

A timer and interrupt management infrastructure is essential for a computer system executing a preemptive operating system. This holds for single- and also for multicore systems. When it comes to OS-capable ISA-heterogeneous multicore systems (systems that include cores of different ISAs, which all are capable of executing an operating system) the different timer and interrupt infrastructures of the different system ISAs are still applicable. However, if reconfigurability is added on top of the ISA heterogeneity, meaning that the composition (number of individual cores) is runtime adaptable, the timer and interrupt management infrastructure needs to be reconsidered. In this paper, a unified timer and interrupt management scheme is deduced for a runtime adaptable, OS-capable, ISA-heterogeneous multi-core system, consisting of ARM and RISC-V cores, that are capable of executing Linux. This is done by analyzing/surveying the timer and interrupt management schemes of RISC-V and ARM systems. Finally this paper will show that RISC-V timer and interrupt management devices are suitable to also manage timers and interrupts for ARM based systems.

In-memory-computing is an emerging approach that aims to shift computational load away from CPUs. It does so by taking over simple calculations that can be performed in memory. Apart from improving performance for these operations, this also results in a lower energy consumption, effectively rendering this technique very suitable for embedded systems. Due to being variable as well as non-volatile resistors, memristors are capable of storing analog values. This renders them particularly useful for in-memory computing. This paper presents a prototypical implementation of analog calculations (addition, subtraction and multiplication), including a way of representing the value zero. The prototype shown is based on an ESP32 microcontroller and typical calculations currently take around 1μs.

Energy optimization in the built environment is receiving more attention in the last decade. This leads to remarkable technological advancements in energy monitoring, data communication, energy storage, control, and data analysis applications. Energy monitoring can be aggregate (Non-Intrusive load monitoring -NILM) or disaggregate (Intrusive load monitoring -ILM) based on the location in which the monitoring takes place. Sensors communicate via wired or wireless means, and several protocols are developed to support communications in smart homes. This real-time data can be sent to remote controllers for further analysis, training and prediction applications using Internet of Things (IoT) that provides a cost-effective solution for energy management systems. This manuscript presents an overview of current innovation in smart homes for the advancement of building technology.

The upcoming topic of in-memory-computing tries to support CPUs by taking over simple calculations that can be done in memory. This leads to less performance drain caused by those simple calculations as well as lower energy consumption for the whole system, which is particularly important for embedded systems.

Many embedded systems reside within bigger electrical systems. While the embedded system takes control over many aspects of the surrounding systems, the amount of possible control is set by the given configuration. This causes a divide between the flexibility provided by software and the unchanging nature of the encompassing hardware. The concept of programmable circuits seeks to bridge this gap. The use of memristors enables the changing of resistor values within a circuit without disassembly. The continuous, non-volatile variable resistor provides the possibility to reconfigure hardware circuits through external influences or even by software on the embedded system at run time.

In the last decade, the significant development of smart building technologies has led to the formation of various energy sensing and monitoring applications. Energy monitoring of appliances relies on techniques such as Intrusive Load Monitoring (ILM) and Non-Intrusive Load Monitoring (NILM). ILM is referred to a technique that a sensor installed for each load. In NILM method, disaggregation of measured energy of all appliances at utility service entry is the main goal to provide a simple and cost-effective method of monitoring the appliances like sequence time domain reflectometry (STDR). This manuscript provides an overview of developments in energy consumption sensing and monitoring in three key areas of Internet of things (IoT), WSN and STDR for the advancement of smart building technology. This paper also provides some research directions for smart home of the future.

Recent trends in the applications of batteries in the built environment are improving the efficiency of batteries and lowering costs. This paper introduces various types of battery technologies such as sodium sulfur, lithium ion, flow and lead acid batteries and discusses their models. Various applications of batteries such as adaptive battery systems, Battery Electrical Vehicles (BEVs), Battery Energy Storage Systems (BESS), the Internet of Things (IoT), and Smart Grid and Smart Environment applications are also discussed. In their selection and use of batteries, scholars are ultimately looking to maximize occupant comfort whilst keeping costs low and optimizing the energy efficiency of buildings. This paper will provide a review of current trends in this field.

In the past the security of building automation solely depended on the security of the devices inside or tightly connected to the building. In the last years more devices evolved using some kind of cloud service as a back-end or providers supplying some kind of device to the user. Also, the number of building automation systems connected to the Internet for management, control, and data storage increases every year. These developments cause the appearance of new threats on building automation. As Internet of Thing (IoT) and building automation intertwine more and more these threats are also valid for IoT installations. The paper presents new attack vectors and new threats using the threat model of Meyer et al.[1].

Synthesizing hardware from a Hardware Description Language (HDL) for Field Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs) is very important today because many companies produce ASICs or use FPGAs for prototyping or High Performance Computing (HPC). Although, the synthesis, mapping and routing processes are well understood and good covered by research, some challenges in the operation of these processes exist, such as easy design space exploration, commercial license management, and different software version support which are not focus of research yet. This paper addresses these challenges by proposing the outsourcing of the whole hardware synthesis process into the cloud. A complete cloud-based synthesis service is presented consisting out of a command line client to deploy a synthesis process into the cloud, a remote web-service to schedule synthesis jobs within a cluster of servers or virtual machines, and a control webservice on each of these machines to start and stop the synthesis process. This service is evaluated against the standard local synthesis flow.

The Internet of Things (IOT) continues to transform the world, and in many countries is now an integral part of our everyday lives-influencing everything from the way that we intercommunicate to how we conduct business. Innovators continue to find ways to integrate IOT into uses as far flung as fashion to medicine. This survey looks at how IOT is currently being integrated into the built environment for the purpose of saving energy and improving occupants' livelihoods. In particular, it reviews three technologies that have received a lot of attention in the literature as the future of an IOT mediated built environment. Based on this literature, predictions are made of the likely trends in regards to the future scholarship on these technologies.

Security and privacy are very important assets within building and home automation because the System Control Unit (SCU) stores and processes a huge amount of data about the inhabitants or employees of the building. This data is necessary for managing the building and increasing the convenience of persons within. But this data can also be used to create a movement profile, monitor working times, and draw conclusions about people's health situation. Modern smart home implementations also control many actuators within the building including doors, windows, locks, and fire extinguisher. These increase security and safety, but unauthorized control can reduce the security and can even be harmful to persons. Therefore, identifying the different security and privacy threats is very important and helps system engineers and system managers to develop and deploy secure systems. This work presents an abstract model of a building automation system and some attack trees which simplify threat identification. Attack trees are common in secure software development and secure system deployment. An example smart home deployment is evaluated using the proposed model and attack trees to show the feasibility.

In this paper, an effective low-cost heating, ventilation, and air conditioning (HVAC) control system incorporating a new sensor is proposed. This research builds upon our previous system, which achieved efficient control of the air conditioning (AC) for a large room in a library. By detecting whether or not individual chairs were occupied and regulating the AC near unoccupied chairs, the system reduced the overall power consumption. This detection was achieved using pressure sensors installed in the chairs. However, the sensors required battery power to measure voltage and transmit data. The batteries needed to be replaced within several months, and thus the system required frequent maintenance. In this paper, we introduce a self-powered sensor. The sensor integrates an energy-harvesting switch and a wireless transmitter. The action of pressing or releasing the switch generates sufficient electricity to power the device, and this enables long-term operation without replacing or charging the batteries. When these sensors are integrated into chairs, occupancy status can be detected without additional power or regular maintenance. The proposed improved system with battery-free chair sensors is evaluated in an eight-day experiment conducted at a library in Kurihara, Miyagi Prefecture, Japan. The energy efficiency evaluation indicates that the proposed system can reduce electricity consumption by 18.3%. The predicted mean vote (PMV) values for the environment in the library are determined to assess the comfort level, and these values confirm that the proposed system is capable of maintaining occupant comfort. In the experiment, wireless sensor network is built through the Library to the Laboratory. All sensing data (e.g. temperature, humidity occupancy, status, power consumption, air conditioning status) are managed on the Cloud.

The recent trends in adaptive renewable energy and storage systems for buildings is aiding in improved energy efficiency and costs. Various novel adaptable systems and devices including photovoltaics, batteries and electric vehicles have been proposed in the prior art for the purpose of supporting highly energy sustainable buildings. To aid these systems and to provide additional features, building automation, a trusted technology, is also used to ensure user comfort. Today the challenge is not only to provide comfort, but to do it while having a close eye on the energy performance of the building. Distributed, renewable energy sources, advances in IT and tighter legislative constraints offer and demand changes in the way we operate buildings. This paper will provide a review of current trends in this filed.

To achieve energy efficiency in buildings, a lot of raw data is recorded, during the operation of buildings. This recorded raw data is further used for the analysis of the performance of buildings and its different components e.g. Heating, Ventilation and Air-Conditioning (HVAC). To save time and energy it is required to ensure resilience of the data by detecting and replacing outliers (i.e. data samples that are not plausible) in the data before detailed analysis. This paper discusses the steps involved for detecting outliers in the data obtained from absorption chiller using their On/Off state information. It also proposes a method for automatic detection of On/Off and/or Missing Data status of the chiller. The technique uses two layer K-Means clustering for detecting On/Off as well as Missing Data state of the chiller. After automatic detection of the chiller On/Off cycle, a method for outlier detection is proposed using Z-Score normalization based on the On/Off cycle state of chillers and clustering outliers by Expectation Maximization clustering algorithm. Moreover, the results of filling the missing values with regression and linear interpolation for short and long periods are elaborated. All proposed methods are applied to real building data and the results are discussed.

Partial runtime reconfiguration is a feature of modern Field Programmable Gate Arrays (FPGAs). It allows the reconfiguration of some parts of the FPGA, while other parts are still running and doing computations. The design flow to create a partially run-time reconfigurable system includes the partitioning of a FPGA into multiple collaborating Reconfigurable Modules (RMs), as part of the floor-planning design stage, and the development of an interconnection network. The latency of the chosen interconnection network determines the maximum clock speed the components inside the RMs can run at. The customary way of choosing design constraints to achieve the highest possible speed can lead to very long placement and routing times or even to an un-routable design. Eventually, the the Time To Market (TTM) of a product can be inreased. This paper proposes measuring the latencies of the interconnection network after a relaxed configuration phase. This is achieved by configuring two different kinds of components into the RMs and measure the round trip time of the network between them. Thus, the best placement of reconfigurable components, as well as the maximum clock rate of a given configuration can be calculated, and set without the need to rebuild the system. This enables the developer to place components into the RMs according to their clock speed requirements, without the need to reconfigure or rebuild the full system. This paper also presents some example measurements and an example placement of a small microcontroller.

Smart transportation is an application of intelligent system on transportation domain, expected to bring the society environmental and economic advantages. By combining with IoT techniques, the concept is being enhanced and raised to a system level. Numerous data are able to collect and effective analysis technique is needed. Here in this paper, we proposed a framework of employing IoT technique to construct a free time navigation system. The system aims at providing a real-time quantification of traffic conditions and suggests optimal route based on the information retrieved. The system can be basically separated into two major components: (i) the traffic condition estimation module and the (ii) real-time routing algorithm. In the first component, traffic conditions of roads will be estimated based the information collected from sensors installed on vehicles. Based on these location and speed information, the traffic condition can be quantified using a weighted kernel density estimation (WKDE) function. This function is a function of time and provides a real time insight of the overall traffic condition. By combining this information and the topological structure of the road network, a more accurate time consumption on each road can be estimated and hence enable a better routing.

Homomorphic encryption for smart grids has been investigated in many studies. It is possible to estimate the total power consumption in an area without knowing the consumption data of individual households. In the case of demand response (DR), it is important to calculate the total electric power consumption in an area because DR reports are published accordingly to reduce peak power consumption when the demand is high. However, the published data may reveal private information about residents, such as the timings of specific activities (leaving from and returning home), and device details. To overcome this problem, we propose a method specialized to enable energy providers to securely share electric power consumption data. The proposed method uses a self-organizing map (SOM), which is an unsupervised learning method. In order to share power consumption data while preserving privacy, the SOM is shared without the raw data. In this framework, a target accuracy of nearly 3% is achieved, while actual data are not published by any company.

Building automation is a trusted technology to ensure user comfort in buildings. Today the challenge is not only to provide comfort, but to do it while having a close eye on the energy performance of the building. Distributed, renewable energy sources, advances in IT and tighter legislative constraints offer and demand changes in the way we operate buildings. We look at the core fields that enable building operation: monitoring of operation data, controls, automation and the management organization to show that innovation can be achieved by integrating cross-domain knowledge and getting inspirations from other domains, where existing approaches and technologies can be used and transferred to the domain of building automation.

In this paper a control strategy and sensor concept for a two-wheeled self-balancing robot is proposed. First a mathematical model of the robot is derived using Lagrangian mechanics. Based on the model a full state feedback controller, in combination with two higher-level controls are deployed for stabilization and drive control. A gyroscope, an accelerometer and rotational encoders are used for state determination, introducing a new method of measurement data fusion for the accelerometer and the gyro by using a drift compensation controller. Furthermore measurement proceedings for the model parameters of a real prototype robot are suggested and the control for this robot is designed. The proposed mathematical model, as well as the control strategy are then verified by comparing the behavior of the constructed robot with model simulations.

So far the worlds of building automation and power networks have co-existed electrically attached but without data interaction, with different, and sometimes divergent, goals and requirements. The smartgrid community is coping nowadays with a new phase in the deployment of its vision: the integration of smart buildings, making use of their services and advantages to enable more complex functionalities at a global level. The main objective of this paper is to review latest results of the research community of industrial electronics, whose society within the IEEE, the IES, acts as the organizer of this conference. At the conference, latest advances and developments in design, modelling, simulating and implementing tools for, or systems of, sensor and/or actuator networks with advances towards user orientation, wireless connectivity, dependability, energy efficiency, context awareness and ubiquitous computing will be presented.

This paper describes a framework for the identification of household appliances based on a measured aggregated load profile. Device activation and deactivation events are detected by a set of non-intrusive algorithms collected in the software structure. These detections are then matched to a database of load values. The result which is basically a detection probability in combination with consumption data of the device, is displayed to the customer as energy feedback. This motivates users to apply energy-saving measures, or in combination with an home automation system appliances can be turned off automatically. Another concept is to implement more intelligence directly into the devices. Such smart appliances communicate with an energy management gateway and plan their activation autonomous. For the proof of concept a simulator for smart home appliances was developed and integrated into a demonstration setup. Finally the discussed results suggest that disaggregated energy feedback in combination with smart home appliances is a feasible approach in order to using the available energy in a more efficient way.

Previously mostly independently considered topics grow more and more together to form the building blocks of the future smart city. The building itself needs to be built as a zero average energy consuming building, posing requirements mainly on thermal and electrical parameters. Those parameters need to be known and controlled, requiring intelligent control techniques and cross-layer optimized sensor networks. Finally, very differently used buildings together participate in the infrastructure of the city, which gives them freedom to passively burden the grids, or actively help stabilizing them, while benefitting from different tariffs in the smart grids. This paper summarizes the state of the art of those topics with respect to industrial electronics.

In this paper, we propose a human daily activity recognition method that is used for Ambient Assisted Living. The proposed system is able to learn a user's activities using the data from motion and door sensors. We extract low level features from the sensor data and feed the features to a model that combines support vector machines (SVMs) and conditional random fields (CRFs) to give accurate recognition results. We propose to combine SVM and CRF classifiers in a hierarchical model which results in better accuracies and can also make use of high level features. We conducted experiments and presented the effectiveness and accuracies of the proposed method.

Wireless communication in a car has several advantages, given that demanded safety and real-time requirements are fulfilled. This paper presents a wireless MAC protocol designed for the needs of automotive and industrial applications. The proposed MAC protocol provides special support for network traffic prioritization in order to guarantee worst-case message delays for a set of high-prioritized nodes. The performance is further analyzed with a network simulator and compared with the IEEE 802.15.4 standard CSMA/CA protocol.

We report an approach targeted to aid design exploration, early decisioning in model refinement, optimization and trade offs. The approach consists of SystemC AMS coupling with a descriptive functional simulator. System engineering tools are typically used in design and analysis of system prototypes captured at very high level. Naturally, in high level analysis accuracy and detail of results is compromised in lieu simulation speed and design effort. In the presented approach, the much needed abstraction and simulation speed is retained during simulation of platform architecture while near implementation models (RTL, SPICE) may be also be cosimulated with the architecture.

Accurate and sufficient design of AMS signal paths is always being a challenge for system designers requiring high simulation performance of the analog model which also incorporates circuit level non-idealities. The new SystemC AMS extensions offer high simulation performance as well as capabilities of incorporating circuit level non-ideal effects. In this paper we modelled a low Over Sampling Ratio (OSR), second order Sigma Delta (ΣΔ) Analog to Digital Converter (ADC) which incorporates non-ideal effects like sampling jitter, kBT/CSnoise, switch non-linearities, band-gap noise and operational amplifier non-idealities (such as finite gain, finite bandwidth, gain nonlinearity, slew rate, leakage and saturation effect). The ADC shows a performance bottle neck of 16 bits. State-of-Art signal conditioning techniques use adaptive correction methods inside the analog part or inside the DSP part of the ADC making it more complicated to realize. In our design we have implemented the adaptive filtration within the micro-controller to correct the noise ground as well as large signal non-linear effects to produce an output which is 20-bits clean, proving sufficiency of low order and low OSR of a ΣΔ ADC for 20 bit resolution as well as a simplified adaptive filtration scheme alleviating the need of adaptive blocks within the ADC.

Networks consisting of many autonomous sensors are gaining importance in real-life applications. Wireless sensor lifetimes still are limited by finite power sources, leading to the need of low-power system designs. A novel holistic approach for system simulation of ultra-low power wireless sensor networks is discussed. Special focus of this paper is parallel modeling of simulation components, adaptive synchronization, power profiling and framework integration. Detailed network power consumption simulation is achieved by not only simulating the sensor nodes—and their various components—themselves, but also the overall system consisting of multiple interacting elements such as a dynamic environment. The framework includes an instruction set simulation in order to enable accurate node simulation as well as extensive power profiling and tracking beyond node borders. The use of adaptive multi-threading leads to considerable hard-and software co-simulation speedup.1

Multi-core processors are about to conquer embedded systems - it is not the question of whether they are coming but how the architectures of the microcontrollers should look with respect to the strict requirements in the field. We present the step from one to multiple cores in this paper, establishing coherence and consistency for different types of shared memory by hardware means. Also support for point-to-point synchronization between the processor cores is realized implementing different hardware barriers. The practical examinations focus on the logical first step from single- to dual-core systems, using an FPGA-development board with two hard PowerPC processor cores. Best and worst-case results, together with intensive bench- marking of all synchronization primitives implemented, show the expected superiority of the hardware solutions. It is also shown that dual-ported memory outperforms single-ported memory if the multiple cores use inherent parallelism by locking shared memory more intelligently using an address-sensitive method.

Modern design of wireless devices requires the designers to have a special focus on power consumption to prolong the battery life of the final system. The designer therefore needs power consumption information very early in the process to be able to decide on system parameters, design methods, communication protocols, functionality restrictions. Typically, this is done by running simulations of the system to be developed and performing design space exploration. However, there is a tradeoff between speed and accuracy of simulation, therefore the designer has to be aware of available tools and simulation methods he can choose from to achieve the best possible solution for his case.

Finite State Machines (FSMs) are a key element of integrated circuits. Hard-coded FSMs do not allow changes after the ASIC production. While an embedded FPGA IP core provides flexibility, it is a complex circuit, requires difficult synthesis tools, and is expensive. This article presents and evaluates a novel architecture that is specifically optimized for implementing reconfigurable finite state machines: Transition-based Reconfigurable FSM (TR-FSM). The architecture shows a considerable reduction in area, delay, and power consumption compared to FPGA architectures with a (nearly) FPGA-like reconfigurability.

Wireless Sensor Networks are gaining more and more importance in various application fields. Often, energy autonomy on the node level is an essential nonfunctional constraint to be met. Therefore, when simulating such networks, the energy consumption on the node level has to be included into the simulation. To make this time consuming task feasible, an overall simulation speedup on the network level is desirable. In this paper, we propose to use techniques similar to those used in Transaction Level Models of Bus Systems.

Recent additions to the system modelling language SystemC, namely SystemC-AMS and OSCI TLM 2.0, provide more efficient ways to model systems within their respective domains. However, most of today’s embedded systems are usually heterogeneous, requiring some way to connect and simulate models from different domains. In this paper we present a first approach on connecting SystemC-AMS models and TLM 2.0 models using temporal decoupling. We show how certain properties of the involved Models of Computation can be exploited to maintain high simulation performance. Using an example to show the feasibility of our approach, we could also observe a certain tradeoff between simulation performance and accuracy. Further on, we discuss semantical issues and decisions that have to be made, when models are connected. As these decisions are typically application-driven, we propose a converter structure that keeps converters simple but also provides ways to model application-specifc behaviour.

Today's heterogeneous embedded systems combine components from different domains, such as software, analogue hardware and digital hardware. The design and implementation of these systems is still a complex and error-prone task due to the different Models of Computations (MoCs), design languages and tools associated with each of the domains. Though making such systems adaptive is technologically feasible, most of the current design methodologies do not explicitely support adaptive architectures. This paper present the ANDRES project. The main objective of ANDRES is the development of a seamless design flow for adaptive heterogeneous embedded systems (AHES) based on the modelling language SystemC. Using domain-specific modelling extensions and libraries, ANDRES will provide means to efficiently use and exploit adaptivity in embedded system design. The design flow is completed by a methodology tools for automatic hardware and software synthesis for adaptive architectures.