Combining GNSS and sensor networks for construction efficiency

January 25th, 2018, Published in Articles: EE Publishers, Articles: PositionIT, Featured: PositionIT

The construction industry faces a number of challenges. Performing under deadline pressure is just one example. More recently, the focus of attention is compliance with emission values. A geomatics approach could help.

The European demolition industry, especially in Germany, must focus on compliance with strict regulations. In the last couple of years it has become easier for residents to file lawsuits because of violations of limit values on construction sites [1]. In order to prevent claims without legal cause, adequate documentation of environmental data is needed. In this context, dust monitoring is of great importance as dust is unavoidable [2]. Noise on construction sites is of particular importance, too.

The aim is to establish a substantial dust-free and noiseless way of working and, consequently to avoid costs such as those imposed by penalties or court-ordered construction halts. In order to improve the related processes, to act more effectively and to tackle further challenges, a satellite-supported concept using sensors will be explained below. It is based on the results of an already completed research project, briefly described below. The new approach aims to increase processes’ efficiency and to carry out analyses on a larger scale. It was developed for the demolition industry, but can also be transferred to other industries.

Overview of current technologies

Before presenting a new approach to solve the issues mentioned above, it is necessary to outline the underlying technologies briefly.

As shown in Fig. 1, the core component is a system to track excavators’ performance by means of GPS. The system was the result of the research project “EPOS” – Efficient process design by satellite-supported software in the earth moving and road construction industry.

Among other elements, the EPOS system consists of GPS antennas and receivers, angle sensors, a tilt sensor and a software component which processes the collected data [3]. The EPOS system can record performance data such as excavated volumes in a certain time span accurately. It is possible to process the collected data further and to provide users with valuable real-time information. The machines’ on-board units provide operators with information to navigate an excavator precisely and transfer data to a central production activity control server (PACS). The PACS supplies current information to stakeholders, such as construction supervisors. Based on this information, current actual-target-comparisons of earthworks are accessible via mobile devices.

Performance issues thus become immediately visible and full transparency of ongoing earthworks is achieved. Further analyses of the collected data are possible. In a multi-layered, closed-loop system, the excavators’ performance data can be enriched with other data, for instance costs of machines, weather data and more. As described in Rausch and Stumpf [4], the results help to identify options to support continuous improvement processes and to avoid future costs. A detailed description of the project results is provided in [3] and [4]. Similar GNSS-based technologies which can be used to track and analyse the performance on construction sites exist for trucks [5; 6], bulldozers [7], asphalt pavers [8] and other construction machines [9, 10].

Fig. 1: Overview of the system with enhancement.

Fig. 1: Overview of the system with enhancement.

The field of sensor technology is progressing at a very fast pace. Through miniaturisation, improved sensitivity, cost reduction and other aspects, sensor technology is advancing into more and more areas. Low-power sensors, the use of energy harvesting, and network technologies in particular, make mobile applications possible. With the possibilities of the Internet of Things (IoT), information fusion of multiple sensors can be accomplished easily.

In the case of the demolition industry, it may become feasible to gather data from all areas of a construction site continuously. Environmental data such as temperature, humidity and moisture can be measured, stored and integrated if necessary. Based on this data, measures can be taken if certain patterns indicate a need for action.

Countermeasures to reduce dust during demolition works are already a necessity in many cases. Compliance with regulatory requirements can be documented if necessary by using optical sensors to measure dust levels. Additionally, it is possible to reduce the countermeasures needed if dust emissions are at an acceptable level. Obligations to keep noise levels down at a minimum can also be documented. By using multiple microphones acoustic events can be recorded and used to pinpoint the exact location of the source [11].

Extending the sensor network

Integration of a sensor network

The EPOS system only allows the manual enrichment of the collected performance data with the environmental data and its transfer to the PACS. For instance, the data representing light and weather conditions has to be added manually by a construction supervisor in an enrichment step.

Using sensor technology, this data can be automatically tracked and processed in future. Additional sensors can also collect further data which was not available for the EPOS system before. Depending on the use case, it is recommendable to assemble an individual set of sensors for the network to gather the desired data.

For our application in the demolition industry, the weather, noise and dust components are important. In different situations other sensors, for instance, to measure air pollutants (such as asbestos) can be also relevant. In this case, we look at environmental pollution affecting local residents, since complaints may arise as a result of exceeded limits. Numerous noise and dust countermeasures have already been developed by construction machinery manufacturers to protect workers [12]. In order to solve the above-mentioned issues for local residents, a sensor network is being set up and integrated into the EPOS system.

The extension of the EPOS system is shown in Fig. 1. Different sensors are combined into sensor boxes. The sensor kits have GPS modules and time-tracking components, so that geospatial and temporal data can be linked to environmental data of the other sensors. These boxes should preferably be located at a place free from interference, and communicate with the PACS, where all data is brought together. It is possible to share this data with other backend systems, for instance, data warehouses or ERP systems. With this satellite-supported sensor network valuable data can be collected and evaluated.

Usage of sensor data

Additional sensors help to gather weather data. They record it automatically and transfer it to the EPOS system, where it is used to extend analysis options. As weather changes usually affect the entire construction site, a single sensor kit is sufficient for most settings. However, in the case of road construction or large-area construction sites, it may be necessary to set up more than one box to track weather data.

To analyse weather data in this case, data on humidity, temperature, rainfall, wind speed and its direction are of interest. Using this data, additional analyses are possible so that construction supervisors will get valuable and up-to-date information. For instance, productivity during rainy conditions can be compared with dry conditions. Furthermore, the level of emissions can be analysed under different weather conditions.

Analyses which consider weather data combined with productivity, downtime or costs help to support planning processes. Weather forecasts can be used to trigger appropriate measures in advance, such as the use of appropriate equipment or rescheduling of tasks. Further analyses of the relationship between weather conditions and environmental impacts can be carried out in combination with dust and noise data. Finally, logged weather data can also help to discuss performances and project progress with the customer, for instance, if construction delays occur because of unforeseen weather conditions.

Technical issues and solutions

The construction of a distributed sensor network is associated with a number of challenges. First of all, it must be guaranteed that the sensors are supplied with sufficient energy. Additionally, the data must be transferred to the control station via a network. To solve these basic issues, technologies such as the s-net of the Fraunhofer Institute can be used. Another option would be the ZigBee specification. In comparison to s-net, however, it reaches its limits when large networks with mobile subscribers and active services are required. S-net establishes energy-saving wireless sensor networks and is designed for distributed data acquisition and collection. The sensor network builds itself up autonomously and transmits data via several, from time-to-time varying, nodes to a gateway [13]. Consequently, the sensor network can be adapted to the respective conditions and dynamically extended by additional nodes.

The sensor boxes should be placed at the edge of the construction site at a height of approximately 2 m for optimal detection. For this purpose, poles can be fixed in the ground and equipped with a sensor box. To mitigate communication breakdowns with the gateway, equip the sensor modules with small storage devices to store data until the connection is re-established. Energy harvesting methods such as energy generation by vibration, conventional battery or cable approaches are all promising options depending on the construction site.

When collecting environmental data, it is essential to comply with the relevant requirements of the responsible authorities. In Germany, for example, sensors and their positioning have to fulfil certain criteria [14]. GPS can be used to make sure and document that their positions are correct. Furthermore, the sensors have to be calibrated and adjusted. For noise measurements, sound pressure level meters have to be enabled for a minimum period of time to calculate average values with significance [14].

Other issues also have to be considered. Due to the compactness of a sensor box, it is easy to steal it. To prevent that, suitable fixing measures must be taken. For this purpose, the fittings or rods used should be mounted as stable as possible and the sensor boxes should be firmly attached. Additionally, sensor information such as GPS signals can be used to detect possible thefts. In case of legal disputes, measures need to be in place to ensure the data cannot be altered fraudulently. Furthermore, employees should not be able to manipulate the system for their own benefit, and the systems should also be protected against manipulation attempts by third parties. In order to do this, each sensor assembly kit’s output should be checked by using a combination of its own data and the data from other sensor boxes. In this way, unrealistic data combinations can be identified and discarded. Encryption should also be used to ensure secure data transmission procedures and compliance with the specific country’s data protection regulations.

Fig. 2: Alpha prototype.

Fig. 2: Alpha prototype.

As a proof-of-concept, a prototype was developed (Fig. 2). A Raspberry Pi (a small single-board computer) equipped with a decibel sensor was used to record sound and convert it into a digital signal via an analogue-to-digital converter. This data can be enriched with GNSS data and further processed by the PACS. Even though more robust components should have been used for a construction site, the first functional tests were promising and the feasibility of the approach could be confirmed. With the functionally-limited prototype it was possible to monitor compliance with noise limits and to analyse the causes of noise.

Evaluation and ongoing work

The successful tests with the prototype showed that it is possible to increase the efficiency of construction works with the extended EPOS system. The system resulted from the need to replace manual inputs with automated measurements and transmissions. More high-quality data can be gathered by the sensor network, such as improved accuracy. With mobile sensor network technology, this approach can be flexibly and quickly adapted to different construction sites with their unique requirements.

Additional benefits result from more efficient dust control and process optimisation. Systems could use the collected data to avoid potential complaints by introducing additional, preventive emission control measures. Thereby, costs and negative publicity can be avoided.

The system also holds advantages for planning and cost control. It makes it is possible to select the most appropriate machine for a specific setting, based on data about the conditions at the construction site. The data can also be used to justify costs to customers and avert or reduce potential contractual penalties.

In implementing the system, the hardware, development and customisation costs should be considered along with ongoing system maintenance costs. Because of the relatively low costs and the expected savings, the system is expected to pay for itself in a relatively short time.

Conclusions and future work

The construction industry has to cope with many challenges. Especially companies in the field of demolition have to deal with issues like compliance with noise and dust limits. Our research in this field resulted in a prototype which combines GPS with additional sensor network technologies. It indicates that the necessary investments in a sensor network to enhance GPS-based performance-tracking systems of construction machines are economically advantageous and make sense.

Emissions can be logged and tracked at a reasonable cost, legal disputes can be avoided, and the collected data can be further analysed. For future studies it may be interesting to add more sensor nodes on the construction site to collect additional data. Data integration makes it possible to create and analyse environmental profiles more precisely, so that the different sources of noise and dust can be tracked and the efficiency of countermeasures be evaluated. Alert systems could inform construction supervisors instantly in case of limit violations and immediate action can be taken. Furthermore, it would be interesting to combine data from different construction sites to improve planning procedures.

In summary, the presented research show that the construction industry could benefit a lot from approaches combining GNSS technologies with sensor networks, and further developments could be promising.


[1] C-J Göpfert (2011): Bauen könnte teurer werden. In: Frankfurter Rundschau, 06-08-2011,, last access on December 21, 2017.
[2] Deutscher Abbruchverband e.V. (Ed.) (2015): Abbrucharbeiten. Grundlagen, Planung, Durchführung. Deutscher Abbruchverband. 3rd Ed. Köln.
[3] P Rausch, F Schreiber, M Diegelmann (2010): New controlling system for earth moving and road construction. In: PositionIT, Aug/Sept 2010.
[4] P Rausch, M Stumpf (2013): Linking the Operational, Tactic and Strategic Levels by Means of CPM: An Example in the Construction Industry. In: Rausch, P./Sheta, A. /Ayesh A. (Eds.): Business Intelligence and Performance Management: Theory, Systems, and Industrial Applications, Springer Verlag U.K., ISBN 978-1-4471-4865-4.
[5] W A Günthner, S Kessler, S Sanladerer (2007): Transportlogistik in der Baubranche – Optimierung durch den Einsatz eines Flottenmanagementsystems. In: Jahrbuch Logistik 2007, free beratung GmbH Korschenbroich, pp. 252-256.
[6] W A Günthner, S Kessler, S Sanladerer (2006): EDV gestützte Fahrzeugdisposition und -abrechung im Baubereich zur Optimierung der Prozesskette. In: Marquardt, H-G (Ed.): Tagungsbeiträge 2. WGTL-Fachkolloquium, Dresden, pp. 17-26.
[7] O Gut (2007): Automatische Steuerung von Baumaschinen mit GPS. In: Der Gartenbau, o. Jg. (43), pp. 2-4.
[8] University of Twente: ASPARi Paving the Way Forward In 2017., last access on December 21, 2017.
[9] B-APS BAUER: Assistant Positioning System,, last access on December 21, 2017.
[10] Leica Geosystems AG: Machine Control for Graders,, last access on December 21, 2017.
[11] V Kumar, J Yan, X Xu, Y Qian, K Soga (2016): Low Power DSP with wireless monitoring for civil constructions. In: RJ Mair, K Soga, Y Jin, AK Parlikad, JM Schooling (Eds.): Transforming the Future of Infrastructure through Smarter Information: Proceedings of the International Conference on Smart Infrastructure and Construction, 27–29 June 2016, ICE Virtual Library, ISBN 978-0-7277-6127-9.
[12] Verlagsanstalt Handwerk GmbH,, last access on December 23, 2017.
[13] Fraunhofer Institut für integrierte Schaltungen IIS (2013), s-net Drahtlose Sensornetze, pp. 2-12,, last access on December 21, 2017.
[14] Bundesregierung/Juris. Allgemeine Verwaltungsvorschrift zum Schutz gegen Baulärm – Geräuschimmissionen., last access on December 21, 2017.

Contact Peter Rausch, Nuremberg Institute of Technology,

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