Efficient Data Management in Agricultural IoT: Compression, Security, and MQTT Protocol Analysis.

The integration of Internet of Things (IoT) technology into agriculture has revolutionized farming practices by using connected devices and sensors to optimize processes and facilitate sustainable execution. Because most IoT devices have limited resources, the vital requirement to efficiently manage data traffic while ensuring data security in agricultural IoT solutions creates several challenges. Therefore, it is important to study the data amount that IoT protocols generate for resource-constrained devices, as it has a direct impact on the device performance and overall usability of the IoT solution.

Nitrogen deficiency in maize: Annotated image classification dataset.

Nitrogen (N) is one of the key inputs in maize production applied in the form of fertilizers. Nitrogen deficiency during the vegetation period leads to lower yields since N is utilized in proteins and enzymes that enable important biochemical processes such as photosynthesis. Nitrogen deficiency leads to specific symptoms that eventually become visible to the naked eye during vegetation.

Performance Evaluation of Container Orchestration Tools in Edge Computing Environments.

Edge computing is a viable approach to improve service delivery and performance parameters by extending the cloud with resources placed closer to a given service environment. Numerous research papers in the literature have already identified the key benefits of this architectural approach. However, most results are based on simulations performed in closed network environments.

Aurora-Trinity: A Super-Light Client for Distributed Ledger Networks Extending the Ethereum Trinity Client.

Light clients for distributed ledger networks can verify blockchain integrity by downloading and analyzing blockchain headers. They are designed to circumvent the high resource requirements, i.e.

Bloom Filter Approach for Autonomous Data Acquisition in the Edge-Based MCS Scenario.

Mobile crowdsensing (MCS) is a sensing paradigm that allows ordinary citizens to use mobile and wearable technologies and become active observers of their surroundings. MCS services generate a massive amount of data due to the vast number of devices engaging in MCS tasks, and the intrinsic mobility of users can quickly make information obsolete, requiring efficient data processing. Our previous work shows that the Bloom filter (BF) is a promising technique to reduce the quantity of redundant data in a hierarchical edge-based MCS ecosystem, allowing users engaging in MCS tasks to make autonomous informed decisions on whether or not to transmit data.

A Regulatory View on Smart City Services.

Even though various commercial Smart City solutions are widely available on the market, we are still witnessing their rather limited adoption, where solutions are typically bound to specific verticals or remain in pilot stages. In this paper we argue that the lack of a Smart City regulatory framework is one of the major obstacles for a wider adoption of Smart City services in practice. Such framework should be accompanied by examples of good practice which stress the necessity of adopting interoperable Smart City services.