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Anna Förster

Publications and source records attributed to Anna Förster.

At least 19 recordsLinked to original sources
arXiv2026

Poster: Camera Tampering Detection for Outdoor IoT Systems

Recently, the use of smart cameras in outdoor settings has grown to improve surveillance and security. Nonetheless, these systems are susceptible to tampering, whether from deliberate vandalism or harsh environmental conditions, which can undermine their monitoring effectiveness. In this context, detecting camera tampering is more challenging when a camera is capturing still images rather than video as there is no sequence of continuous frames over time. In this study, we propose two approaches for detecting tampered images: a rule-based method and a deep-learning-based method. The aim is to evaluate how each method performs in terms of accuracy, computational demands, and the data required for training when applied to real-world scenarios. Our results show that the deep-learning model provides higher accuracy, while the rule-based method is more appropriate for scenarios where resources are limited and a prolonged calibration phase is impractical. We also offer publicly available datasets with normal, blurred, and rotated images to support the development and evaluation of camera tampering detection methods, addressing the need for such resources.

cs.CV↗
arXiv2026

Precise Low-Current Measurement Techniques for IoT Devices: A Case Study on MoleNet

Power consumption is a crucial aspect of IoT devices which often have to run on a battery for an extended period of time. Therefore, supply current measurements are crucial before deploying a device in the field. Multimeters and oscilloscopes are not well suited when it comes to measuring very small currents which occur e.g. when an IoT device is in sleep mode. In this report, we compare dedicated source measurement units (SMUs) which allow to measure very small currents with high precision. As an application example, we demonstrate current measurements on our MoleNet IoT sensor board.

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arXiv2025

ShadowWolf -- Automatic Labelling, Evaluation and Model Training Optimised for Camera Trap Wildlife Images

The continuous growth of the global human population is leading to the expansion of human habitats, resulting in decreasing wildlife spaces and increasing human-wildlife interactions. These interactions can range from minor disturbances, such as raccoons in urban waste bins, to more severe consequences, including species extinction. As a result, the monitoring of wildlife is gaining significance in various contexts. Artificial intelligence (AI) offers a solution by automating the recognition of animals in images and videos, thereby reducing the manual effort required for wildlife monitoring. Traditional AI training involves three main stages: image collection, labelling, and model training. However, the variability, for example, in the landscape (e.g., mountains, open fields, forests), weather (e.g., rain, fog, sunshine), lighting (e.g., day, night), and camera-animal distances presents significant challenges to model robustness and adaptability in real-world scenarios. In this work, we propose a unified framework, called ShadowWolf, designed to address these challenges by integrating and optimizing the stages of AI model training and evaluation. The proposed framework enables dynamic model retraining to adjust to changes in environmental conditions and application requirements, thereby reducing labelling efforts and allowing for on-site model adaptation. This adaptive and unified approach enhances the accuracy and efficiency of wildlife monitoring systems, promoting more effective and scalable conservation efforts.

cs.CV↗
arXiv2024

Empowering IoT Applications with Flexible, Energy-Efficient Remote Management of Low-Power Edge Devices

In the context of the Internet of Things (IoT), reliable and energy-efficient provision of IoT applications has become critical. Equipping IoT systems with tools that enable a flexible, well-performing, and automated way of monitoring and managing IoT edge devices is an essential prerequisite. In current IoT systems, low-power edge appliances have been utilized in a way that can not be controlled and re-configured in a timely manner. Hence, conducting a trade-off solution between manageability, performance and design requirements are demanded. This paper introduces a novel approach for fine-grained monitoring and managing individual micro-services within low-power edge devices, which improves system reliability and energy efficiency. The proposed method enables operational flexibility for IoT edge devices by leveraging a modularization technique. Following a review of existing solutions for remote-managed IoT services, a detailed description of the suggested approach is presented. Also, to explore the essential design principles that must be considered in this approach, the suggested architecture is elaborated in detail. Finally, the advantages of the proposed solution to deal with disruptions are demonstrated in the proof of concept-based experiments.

cs.SE↗
arXiv2024

Comparative Study of Simulators for Vehicular Networks

Vehicular Adhoc networks (VANETs) are composed of vehicles connected with wireless links to exchange data. VANETs have become the backbone of the Intelligent Transportation Systems (ITS) in smart cities and enable many essential services like roadside safety, traffic management, platooning, etc with vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. In any form of research testing and evaluation plays a crucial role. However, in VANETs, real-world experiments require high investment, and heavy resources and can cause many practical difficulties. Therefore, simulations have become critical and the primary way of evaluating VANETs' applications. Furthermore, the upfront challenge is the realistic capture of the networking mechanism of VANETs, which varies from situation to situation. Several factors may contribute to the successful achievement of a random realistic networking behavior. However, the biggest dependency is a powerful tool for the implementation, which could probably take into account all the configuration parameters, loss factors, mobility schemes, and other key features of a VANET, yet give out practical performance metrics with a good trade-off between investment of resources and the results. Hence, the aim of this research is to evaluate some simulators in the scope of VANETs with respect to resource utilization, packet delivery, and computational time.

cs.NI↗
arXiv2023

Using LoRa communication for Urban VANETs: Feasibility and Challenges

Vehicular Ad-Hoc Networks (VANETs) were introduced mainly to increase vehicular safety by enabling communication between vehicles and infrastructure to improve overall awareness. The vehicles in a VANET are expected to exchange numerous messages generated by multiple applications, but mainly, these applications can be subdivided into safety and non-safety. The main communication technologies designed for VANETs, DSRC (Dedicated Short Range Communication) and C-V2X (Cellular V2X), mainly focus on delay-sensitive safety-related applications. However, sharing the same bandwidth for safety and non-safety applications will increase the burden on the communication channel and can cause an increase in the overall latencies. Therefore, this work analyses the feasibility of using LoRa communication for non-safety-related urban VANET applications. We conducted multiple real-world experiments to analyse the performance of LoRa communication in various urban VANET scenarios. Our results show that LoRa communication handles the Dopper shifts caused by the urban VANET speeds with both Spreading Factor (SF) 7 and 12. However, higher SF was more vulnerable to Doppler shifts than lower SF. Furthermore, the results illustrate that the Line-of-Sight (LoS) condition significantly affects the LoRa communication, especially in the case of lower SF.

cs.NI↗
arXiv2023

Reliability Analysis of Monitoring System for Extraterrestrial Habitat using CTMC and Empirical Evaluation

Among the various required resources for this civilization, the habitat is one of the crucial resources to live on Mars. Such an extraterrestrial habitat is designed to provide a safe place to live during the initial missions. It is equipped with monitoring and life support systems to ensure the astronauts' safety. In this work, we present a robust monitoring system with a use case for extraterrestrial habitats. Similar to a typical monitoring system, it consists of sensor nodes and a gateway connected through a wireless communication channel. In our system, we introduce robustness to various failures that can occur after deployment, namely, board, sensor and gateway failure, in the form of redundancy. For each failure, the problem is tackled differently. For the first two types, we use additional hardware as backup, while for the last type, we use neighbouring devices as backups. The backup devices function as replacements for the failed component, which helps the system to collect the data which would otherwise be lost. We evaluate how much the performance of the system improves by using backup devices. We use a Continuous-Time Markov chain for the theoretical evaluation and an experimental setup that includes the hardware prototype for the empirical evaluation. We also analyze the effect of a simple medium access mechanism on the system's performance in the presence of heavy noise on the channel. Based on our requirements, we use a simple custom medium access control (MAC) algorithm called Slotted-ALOHA with Random Back-off (SARB) to make communication reliable. We demonstrate that around $30-34\%$ of the packets are recovered, with the use of backup devices (redundancy), which would otherwise be lost in case of failures. We also demonstrate that the system's performance improves by $3.8-13.2\%$ with the use of a simple medium access technique (SARB).

eess.SY↗
arXiv2021

Machine Learning based Soil VWC and Field Capacity Estimation Using Low Cost Sensors

The amount of water present in soil is measured in terms of a parameter commonly referred to as Volumetric Water Content (VWC) and is used for determining the field capacity of any soil. It is an important parameter accounting for ensuring proper irrigation at plantation sites for farming as well as for afforestation activities. The current work is an extension to already going on research in the area of wireless underground sensor networks (WUSNs). Sensor nodes equipped with Decagon 5TM volumetric water content (VWC) and temperature sensor are deployed underground to understand the properties of soil for agricultural activities. The major hindrances in the deployment of such networks over a large field are the cost of VWC sensors and the credibility of the data being collected by these sensors. In this paper, we analyze the use of low-cost moisture and temperature sensors that can either be used to estimate the VWC values and field capacity or cross-validate the data of expensive VWC sensors before the actual deployment. Machine learning algorithms, namely Neural Networks and Random Forests are investigated for predicting the VWC value from low-cost moisture sensors. Several field experiments are carried out to examine the proposed hypothesis. The results showed that low-cost moisture sensors can assist in estimating the VWC and field capacity with a minor trade-off.

eess.SP↗
arXiv2018

Simulating Opportunistic Networks: Survey and Future Directions

Simulation is one of the most powerful tools we have for evaluating the performance of Opportunistic Networks. In this survey, we focus on available tools and models, compare their performance and precision and experimentally show the scalability of different simulators. We also perform a gap analysis of state-of-the-art Opportunistic Network simulations and sketch out possible further development and lines of research. This survey is targeted at students starting work and research in this area while also serving as a valuable source of information for experienced researchers.

cs.NI↗
arXiv2017

Opportunistic Networking Protocol Simulator for OMNeT++

The number of computing devices of the Internet of Things (IoT) is expected to grow by billions. New networking architectures are being considered to handle communications in the IoT. One of these architectures is Opportunistic Networking (OppNets). To evaluate the performance of OppNets, an OMNeT++ based modular simulator is built with models that handle the operations of the different protocol layers of an OppNets based node. The work presented here provides the details of this simulator, called the Opportunistic Protocol Simulator (OPS).

cs.NI↗
arXiv2017

Reactive User Behavior and Mobility Models

In this paper, we present a set of simulation models to more realistically mimic the behaviour of users reading messages. We propose a User Behaviour Model, where a simulated user reacts to a message by a flexible set of possible reactions (e.g. ignore, read, like, save, etc.) and a mobility-based reaction (visit a place, run away from danger, etc.). We describe our models and their implementation in OMNeT++. We strongly believe that these models will significantly contribute to the state of the art of simulating realistically opportunistic networks.

cs.NI↗
arXiv2017

Radio Irregularity Model in OMNeT++

Radio irregularity is a non-negligible phenomenon that has an impact on protocol performances. For instance, irregularity in radio range leads to asymmetric links that cause the loss of packets in different directions. In order to investigate its effect, the Radio Irregularity Model (RIM) is proposed that takes into account the irregularity of a radio range and estimates path losses in an anisotropic environment. The purpose of this paper is to provide details of the RIM model developed in the INET Framework of the OMNeT++ simulator that can be used to investigate the impact of radio irregularity on protocol performance.

cs.NI↗
arXiv2016

Implementation of the SWIM Mobility Model in OMNeT++

The Internet of Things (IoT) is expected to grow into billions of devices in the near future. Evaluating mechanisms such as networking architectures for communications in the IoT require the use of simulators due to the scale of the size of networks. Mobility is one of the key aspects that need to be evaluated when considering the different scenarios of the IoT. Small Worlds in Motion (SWIM) is a mobility model that mathematically characterises the movement patterns of humans. The work presented in this paper details the development and verification of the SWIM mobility model in the OMNeT++ simulator.

cs.NI↗
arXiv2015

OMNeT++ and mosaik: Enabling Simulation of Smart Grid Communications

This paper presents a preliminary system architecture of integrating OMNeT++ into the mosaik co-simulation framework. This will enable realistic simulation of communication network protocols and services for smart grid scenarios and on the other side, further development of communication protocols for smart grid applications. Thus, by integrating OMNeT++ and mosaik, both communities will be able to leverage each others's sophisticated simulation models and expertise. The main challenges identified are the external management of the OMNeT++ simulation kernel and performance issues when federating various simulators, including OMNeT++ into the mosaik framework. The purpose of this paper is to bring these challenges up and to gather relevant experience and expertise from the OMNeT++ community. We especially encourage collaboration among all OMNeT++ developers and users.

cs.NI↗
arXiv2015

Federating OMNeT++ Simulations with Testbed Environments

We are in the process of developing a system architecture for opportunistic and information centric communications. This architecture (called Keetchi), meant for the Internet of Things (IoT) is focussed on enabling applications to perform distributed and decentralised communications among smart devices. To realise and evaluate this architecture, we follow a 3-step approach. Our first approach of evaluation is the development of a testbed with smart devices (mainly smart phones and tablets) deployed with this architecture including the applications. The second step is where the architecture is evaluated in large scale scenarios with the OMNeT++ simulation environment. The third step is where the OMNeT++ simulation environment is fed with traces of data collected from experiments done using the testbed. In realising these environments, we develop the functionality of this architecture as a common code base that is able to operate in the OMNeT++ environment as well as in the smart devices of the testbed (e.g., Android, iOS, Contiki, etc.). This paper presents the details of the "Write once, compile anywhere" (WOCA) code base architecture of Keetchi.

cs.NI↗