In this article, we introduce an energy harvesting system capable of converting bipolar thermal gradients to electrical energy. An active rectification circuit, impedance matching, and commodity thermoelectric generators are used efficiently extract from very small temperature found at the natural ground-to-air boundary. The full is modeled in detail radiation load. This end-to-end model enables dimensioning meet specific application requirements. A multiyear deployment supplying a wireless...

Indoor energy harvesting has recently enabled long-term deployments of sustainable IoT sensor nodes. The performance such systems operating in an energy-neutral man-ner can be optimized by exploiting prediction models. Numerous algorithms have been developed, yet they are primarily intended for outdoor (solar) harvesting. environments much more challenging to predict since the primary is very variable. We propose a method based on random forests that capable capturing and predicting this...

Employing energy harvesting to power the Internet of Things supports their long-term, self-sustainable, and maintenance-free operation. These systems have an management subsystem orchestrate flow optimize achievable system performance. Numerous such algorithms for a single harvesting-based been proposed. When envisioning joint use multiple distributed nodes in application, performance behavior depends on mutual availability therefore all nodes. We propose perform jointly thus, system's as...

Internet of Things (IoT) systems can rely on energy harvesting to extend battery lifetimes or even render batteries obsolete. Such employ an scheduler optimize their behavior and thus performance by adapting the node operation. Predictive models sources, which are inherently non-deterministic consequently challenging predict, often necessary for performance. Therefore accuracy predictive model inevitably impacts system This fact has been largely overlooked in vast amount available results...

Internet of Things (IoT) systems can rely on energy harvesting to extend battery lifetimes or even render batteries obsolete. Such employ an scheduler optimise their behaviour and thus performance by adapting the system's operation. Predictive models sources, which are inherently non-deterministic consequently challenging predict, often necessary for performance. Because inaccurate predictions utilised scheduler, predictive model's accuracy inevitably impacts system This fact has largely...

This paper considers the control of uncertain systems operated under limited resource factors, such as battery life or hardware longevity.We consider here resource-aware self-triggered techniques that schedule system operation non-uniformly in time order to balance performance against consumption.When running an environment, unknown disturbances may deteriorate by acting adversarially planned event triggering schedule.In this work, we propose a stochastic predictive scheme tackle challenge,...

Data sharing is crucial for building large datasets which in return are essential developing and training accurate models many contexts including smart cities, agriculture, medical applications. However, shared data may leak private information, such as personal identifiers or location. Past research provides evidence that solely removing these through pseudonymization not enough to ensure privacy protection, since even the pseudonymized still contain information about provider. In this...

Wireless sensors form an integral part of the Internet Things (IoT), standing at edge between cyber and physical domains. Ac-quiring transmitting environmental data is energy-intensive workload, especially when considering networks spanning large buildings or even cities. Many works aim to integrate energy har-vesting into wireless sensors, providing them with a greater level autonomy. Initially deployed for energy-rich outdoor environments, recent advances have allowed efficiently utilize...

Short-range multi-hop communication is an energy-efficient way to collect, share, and distribute large amounts of data with Internet Things (IoT) systems. Nevertheless, the resource demands wireless impose a burden on battery-operated IoT nodes, limiting their lifetime. Energy harvesting can address energy limitation but introduces significant power variability, which affects reliable operation causing nodes disconnect join network repeatedly. To mitigate this, we present Dual-Range...

Batteryless sensors have recently been proposed as an energy-efficient and cost-effective alternative to battery-powered sensors. By harvesting immediately consuming ambient energy, it becomes unnecessary design systems with large energy storages, which significantly increases their form factor, cost, environmental impact. Many works focused on designing batteryless that sense data, process it, wirelessly broadcast processed data. Yet wireless security aspects of applications are only now...

The wide adoption of wireless devices in the Internet Things requires controllers that are able to operate with limited resources, such as battery life. Operating these robustly an uncertain environment, while managing available increases difficultly controller design. This letter proposes a robust self-triggered model predictive control approach optimize objective resource consumption. In particular, novel zero-order-hold aperiodic discrete-time feedback law is developed ensure constraint...

With the Internet of Things (IoT) large amounts data can be gathered at edge, centrally collected and subsequently utilized for various application domains. Efficient reliable synchro-nous communication protocols are essential automated gathering, yet they typically require a stable energy supply. En-ergy harvesting enables long-term deployments, but it imposes widely varying budgets on each node in network. To re-main efficient, synchronous need to consider this variability. We propose...

Distributed embedded systems are pervasive components jointly operating in a wide range of applications. Moving toward energy harvesting powered enables their long-term, sustainable, scalable, and maintenance-free operation. When these used as an automatic control system to sense plant, availability limits when how often sensed data obtainable therefore updates can be performed. The time-varying non-deterministic harvested the necessity plan usage sensor nodes ahead time, on one hand, have...

In this work, we show that sensor data may leak a sensor's location even if the latter is not explicitly included in set. The sensors are localized by linking data, particular activity with publicly available environmental such as weather data. We using linkage attack cow can be within an entire country average accuracy of up to 32.6 km solely from traces recorded tracker cow's stomach.

This paper considers the control of uncertain systems that are operated under limited resource factors, such as battery life or hardware longevity. We consider here resource-aware self-triggered techniques schedule system operation non-uniformly in time order to balance performance against consumption. When running an environment, unknown disturbances may deteriorate by acting adversarially planned event triggering schedule. In this work, we propose a stochastic predictive scheme tackle...

The wide adoption of wireless devices in the Internet Things requires controllers that are able to operate with limited resources, such as battery life. Operating these robustly an uncertain environment, while managing available increases difficultly controller design. This paper proposes a robust self-triggered model predictive control approach optimize objective resource consumption. In particular, novel zero-order-hold aperiodic discrete-time feedback law is developed ensure constraint...