Month: June 2020

The SWAMP project recently published a paper in the IEEE Latin-American Conference on Communications (LATINCOM 2019), reporting an early experience with data quality assurance for IoT-based smart applications. Foundations of Data Quality Assurance for IoT-based Smart Applications provides a framework for data quality assurance in the IoT-base smart applications end-to-end data flow and reports the results of preliminary experiments using a long term raw sensor data provided by a partner company working with intelligent crop services.

The IoT and Big Data contemporary context brings several challenges, such as providing quality assurance (defined by availability and veracity) for sensor data. This paper proposes a discussion on the adequate foundations of a new general approach aimed at increasing the robustness and antifragility of IoT-based smart applications. Besides, it shows results of preliminary experiments with real data in the context of precision irrigation using multivariate methods to identify relevant situations, such as sensor failures and the mismatch of contextual sensor information due to different spatial granularities capture.

We used LOF (Local Outlier Factor algorithm), one of the most successful anomaly detection techniques for modern Big Data environments. LOF is a multidimensional anomaly detection technique for computing spatial density and providing real numerical value for each data point.

Filled circles denote a behavior considered typical by LOF, whereas points in other shapes represent anomalous behavior. Red triangles represent the soil is previously dry, with no relevant precipitation, although an extreme jump of water availability is observed in the soil, which is highly unexpected. Blue crosses represent significant soil drying jumps, when the expected behavior is a smoother drying process, even for days with no precipitation. Purple stars represent extreme cases of the blue crosses, where soil water availability is high, but the soil dried entirely in only one day, a highly unexpected phenomenon.

The SWAMP project recently published a paper in the IEEE Global Humanitarian Technology Conference (GHTC 2019), reporting an early attempt to build a digital twin for smart agriculture. A Digital Twin for Smart Farming leverages the technologies developed by SWAMP and Smart Sensing projects by creating an initial digital environment to provide farmers with a better understanding of the resources and equipment in their farms.

This paper presents a digital twin in the agriculture domain by leveraging the technologies developed by Sensing Change and the Smart Water Management Platform projects. The Sensing Change project developed a soil probe, whereas the SWAMP project is currently developing an Internet of Things platform for water management in farms. This paper leverages the technologies developed by those projects by building an initial digital environment to create a cyber-physical-system (CPS) so farmers can better understand the state of their farms regarding the use of resources and equipment. We conclude that our system can gather data from the soil probe and display its information in a dashboard, enabling the further deployment of more soil probes and other monitoring and controlling devices to create a fully operating digital twin.

The system consists of a field-installed probe that collects information on air temperature and humidity (DHT22), ambient light (BH1750), geospatial position (Venus GPS), the ground temperature at 7 cm depth (DS18B20), and soil moisture at depths of 7cm, 28cm, 50cm and 72cm (CSMv1.2). Probe signals are sent to a Raspberry Pi-3 module using: I2C bus (CSM v1.2 and BH1750); GPIO (DHT22); serial bus (Venus GPS); and One-Wire bus (DS18B20). An ADS1115 module is also used for the CSMv1.2 A/D signal conversion

A first experiment indicates that the probe can send data to the cloud and that it is possible to show this data in a real-time dashboard. It is noticeable that there is an abnormal drop in air humidity and air temperature, which indicates a hardware and communication problem that should be further addressed.

The SWAMP project published a paper in the Workshop of Cloud Networks (WCN 2019) promoting openness as a critical factor for providing interoperability and facilitating the interaction of new and existing pieces of an end-to-end IoT smart application. Designing an Open IoT Ecosystem advocates that the promotion of collaboration for building a healthy IoT ecosystem will be highly influenced by various levels of openness of the solutions, such as open-source, open platform, open services, open data, and open knowledge

We identify different possibilities for an end-to-end IoT Smart Application to deal with the three phases of an Input-Process-Output Model. In the center, we represent the SWAMP approach for the Intercrop pilot. It is also currently the most common one, where the platform must be developed, and sensors and actuators must be controlled directly by the platform. This picture also illustrates different interactions in an Open IoT Ecosystem. The bottom strip depicts an end-to-end system where sensing, platform, and irrigation belong to the same company. Furthermore, there might be a variety of platforms that provide and use different services among each other.

The picture below represents only one possibility in the specific case where the input (sensing), process (platform), and output (irrigation) belong to different organizations.