Wireless Sensor Network for Environmental Monitoring of Cultural

Heritage

Adri

an Hinostroza

and Jimmy Tarrillo

Department of Electrical Engineering, Universidad de Ingenier

ıa y Tecnolog

ıa, Lima, Peru

Keywords:

Heritage, WSN, BLE, ZigBee, Wi-Fi, GPRS.

Abstract:

Cultural heritage assets represent the history and unique identity for every nation in the world, so their pro-

tection and conservation are mandatory tasks. However, although such assets are usually exhibited in special

museum rooms, sometimes the environmental conditions may be modiﬁed, putting the materials at risk. These

facts can be more severe in warehouses, where environmental conditions can vary even more. Most of the mea-

surement sites are located in spaces that make it difﬁcult or do not allow the handling of commercial devices

for measuring multiple environmental parameters, either due to their size, energy consumption or because

they cannot be connected to the internet, so there is no timely availability of information on the environmental

condition in which they are found. This work presents the design and implementation of a wireless sensors

network based on Bluetooth Low Energy and ZigBee, able to measure temperature, moisture, light intensity

and irradiance, and particulate matter 2.5 and 10, in the different spaces where objects of cultural heritage are

found. These measurements are sent to a web platform through the use of Wi-Fi or GPRS technology.

1 INTRODUCTION

Due to the great impact of environmental factors on

the deterioration of materials, the monitoring of these

factors is essential for making risk management de-

cisions and for establishing preventive conservation

strategies for heritage assets (Morales, 2000). Envi-

ronmental data collection equipments can have two

forms of storage, real and remote. While local stor-

age (in the device itself) uses robust and consolidated

technologies, viewing or downloading the collected

information requires the presence of the people in

charge and, in emergency cases (for example, during

lockdowns) it is not possible to access information to

take conservation decisions. Instead, remote storage

devices allow data to be sent to a cloud, from which it

can be accessed from anywhere in the world. This re-

quires relatively new connectivity technologies since

they depend on the physical and technological infras-

tructure of the place. In addition, they depends on

the presence of networks that allow access to remote

servers since they require Internet connectivity like

Wi-Fi or Ethernet cable.

The collection of information on environmental

parameters is essential for decision-making in preven-

https://orcid.org/0000-0001-8570-4098

https://orcid.org/0000-0001-5140-7984

tive conservation. There are some limitations in this

regard that includes: infrastructure that makes it difﬁ-

cult to install monitoring equipment with low auton-

omy or that requires electrical wiring since constant

labor will be needed to be able to give it the respec-

tive maintenance; limited number of personnel trained

in-situ to manage the information collected; the loca-

tion of the assets to be monitored (both geographi-

cally and inside the building itself) as this can bring

connectivity limitations; the huge diversity of the her-

itage that implies the need to use different sensors that

allow measuring different environmental parameters

corresponding to the most relevant for each type of

material. All of these facts make it impossible for re-

searchers to know the environmental conditions of the

places where they save or conserve the heritage.

In the literature we can ﬁnd some environmental

monitoring systems developed for heritage conserva-

tion. In (Tse et al., 2018) the authors developed a

remote particulate matter measurement system for the

care of collections in museums and sensors send mea-

sured data directly to an AWS EC2 server over Wi-Fi.

As we can see, they do not include more sensors in

their system and since the sensors send data directly

to server, the autonomy of the system is low. In (Al-

suhly and Khattab, 2018; Tse et al., 2020) the authors

present the design of a WSN with a complete sen-

Hinostroza, A. and Tarrillo, J.

Wireless Sensor Network for Environmental Monitoring of Cultural Heritage.

DOI: 10.5220/0010916700003118

In Proceedings of the 11th International Conference on Sensor Networks (SENSORNETS 2022), pages 171-175

ISBN: 978-989-758-551-7; ISSN: 2184-4380

171

sors set including temperature, humidity, light, accel-

eration and presence by using IR sensor. In this sys-

tem, a Raspberry Pi gateway establishes the connec-

tion among the nodes and the server through Wi-Fi.

The results show that the lifetime is approximately 9.8

days with the use of three 600 mAh batteries since the

use of a high-power system like Raspberry. The sys-

tems in (Shah and Mishra, 2016; Peralta et al., 2010)

works with a local server where the data is saved con-

tinuously. This implementation difﬁcult to achieve a

timely conservation work. The works in (Al-Habal

and Khattab, 2019; Eltresy et al., 2019; Zhang and

Ye, 2011; Viani et al., 2014) shows the use of WSN

by using IEEE 802.15.4 standard communication like

ZigBee or ISM bands. These implementations were

performed until a ﬁrst stage of prototyping, so if these

systems were used in real places for a long time, they

would not work properly.

Therefore, the proposal of this work is based on

the basic requirements that monitoring devices must

have in the context of heritage conservation. These

requirements include long autonomy for low main-

tenance; Wide set of sensors and remote data avail-

ability that do not depend on the physical and tech-

nological infrastructure of the place. Thus, this work

presents the design and implementation of a wireless

sensor network based on peripheral and central nodes.

In addition, to improve usability, we proposed the de-

velopment of modular hardware and an easy-to-use

online platform.

This paper is divided as follows: in Section II we

described some considerations that were made dur-

ing the design process; in Section III we describe the

methods and tools used to accomplish the objectives

of this work; in Section IV is focus on the results and

ﬁnally, we present the conclusions in Section V.

2 DESIGN CONSIDERATIONS

In order to develop the whole proposed system (hard-

ware and software), in this Section we describe the

considerations used to achieve the objectives of this

work.

2.1 Long Autonomy

In order to achieve low maintenance on the hardware,

it is necessary for it to remain operational for a long

time depending on the sample rate of the environmen-

tal parameter measurements. Since the devices are

battery powered, this consideration is the most impor-

tant.

2.2 Wide Sensors Set

Given the huge diversity of the heritage, it implies the

need to use different sensors that allow measuring dif-

ferent environmental parameters corresponding to the

most relevant for each type of material. The most rel-

evant environmental parameters are temperature, rela-

tive humidity, illuminance, irradiance and particulate

matter. So the devices should be capable of measure

all these parameters.

2.3 Remote Data Availability

This consideration implies the use of Internet connec-

tivity. Due to the geography location and the infras-

tructure of the building where the heritage is found,

the Internet connectivity must remain constant or at

least, it must be available when data needs to be up-

loaded. Due to this consideration, it is important to

the develop a system capable of guaranteeing the In-

ternet connection in the devices.

3 METHODOLOGY

The project starts from the recognition of the needs of

a group of museums and archaeological sites, from

which the most relevant parameters are known ac-

cording to the researchers or those responsible for

maintaining a collection. Then, the required sensors

are acquired and it is decided to build networks of

environmental monitoring systems (nodes) capable of

working with a speciﬁc type of connectivity. Each

network has a central node and several peripheral

nodes; the peripheral nodes send information to the

central node through a local wireless network (BLE or

ZigBee). The central node is responsible for sending

it to a online platform using WiFi or GPRS. The nodes

can include sensors for temperature, relative humid-

ity, iluminance, irradiance and particulate matter. The

hardware of the proposed system allows the coupling

and decoupling of various sensors, as well as wire-

less communication modules, in such a way that the

monitoring systems developed can be adapted to dif-

ferent needs and realities. We divided the methodol-

ogy in hardware and software development and it is

described following the schematic shown in Figure 1.

3.1 Hardware Development

In this section we will describe the design and imple-

mentation of the system’s hardware. The hardware

includes electrical, mechanical, electronics compo-

nents, sensors ICs, wireless modules and batteries.

SENSORNETS 2022 - 11th International Conference on Sensor Networks

172

Figure 1: System Schematic Diagram.

The modular hardware proposed allows to have a

single physical device with two functionalities within

the wireless sensor network (WSN): central node and

peripheral node. Also, if a device is used as a periph-

eral node, it may have one or more sensors included.

It allows the user to have a versatile and more simpli-

ﬁed device to use, since they can choose the compo-

nents (sensors and wireless modules) that they want

to have in a certain application. The use of Board-

to-board (B2B) connectors were used in order to per-

form this feature in the hardware. The mainboard is

where the sensors and wireless module can be cou-

pled and decoupled from. It is mainly based on an AT-

mega1284P 8-bit microcontroller, a M24M01 EEP-

ROM memory from ST, an external TPL5110 timer

and a FTDI UART-to-USB bridge IC with micro-USB

connector.

The table 1 presents the list of sensors and wire-

less modules used for this application. The sensors

were chosen by considering low power consumption,

reduced size and high accuracy. The wireless modules

where chosen by considering the range, RF power and

communication protocol. ZigBee was chosen as long

range alternative for BLE, so it is used in places where

a long range WSN is needed.

The devices are powered by 1600 mAh Li-Ion bat-

teries in 2S1P conﬁguration. Even though all devices

have batteries, the devices meant to be used as central

node need to be plugged into the wall due to the high

consume they require. However, if the wall power

fails, these devices will remain alive up to three hours.

3.2 Software Development

The system software consists of the online platform

and the ﬁrmware that has been programmed on the

microcontroller. The ﬁrmware is unique for all the

twenty devices developed since, being modular hard-

ware, it must contain the operating algorithm for

both the central and peripheral nodes. Although, the

ﬁrmware is different when using ZigBee or BLE due

to the incompatible I/O pins.

The online platform was implemented by using

Amazon Web Services (AWS) and the architecture di-

agram is presented in Figure 2. The platform was de-

signed for HTTP connections with the devices over

the Internet and the users can access by using a PC or

mobile phones. The platform back-end is capable of

storing data and allow many connections from users

and devices. The platform front-end was designed by

using HTML, CSS and JavaScript.

Figure 2: Architecture diagram of the online platform in

AWS.

4 RESULTS

A total of 20 environmental monitoring nodes have

been developed, from which various networks can be

set up depending on the requirements of a speciﬁc lo-

cation. From these, 10 nodes have direct connection

capability to the Internet, in such a way that up to 10

networks could be made, each one with a peripheral

node. These systems have already been preliminarily

evaluated and the possibility of receiving data on en-

vironmental parameters remotely has been conﬁrmed.

During the system testing, we structured the devices

as shown in Figure 3, where we can ﬁnd six networks:

5 BLE networks with 3 nodes each one; and 1 ZigBee

Network with 5 peripheral nodes.

The dimensions of the devices are

155.5x53.8x38.8 mm (Figure 4) . The system

has an autonomy of 5 months using 30 minutes of

sampling rate. Each node (peripheral and central) has

sensors to measure temperature, relative humidity,

illuminance and irradiance; and up to 5 central nodes

Figure 3: Networks Structure during testing.

Wireless Sensor Network for Environmental Monitoring of Cultural Heritage

173

Table 1: List of sensors and wireless modules.

Type Part number Manufacturer Description

Sensor

SHT40 Sensirion Temperature and RH sensor

OPT3001 TI Iluminance sensor

OPT3002 TI Irradiance sensor

SPS30 Sensirion PM sensor

Wireless module

RN4020 Microchip BLE module

E18-MS1-PCB Ebyte ZigBee module

ESP32 Espressif WiFi module

SIM800L SIMCOM GPRS module

Figure 4: Hardware designed.

have the capacity to measure particulate matter. Each

sensor is physically removable from the mainboard

of each node due to the adaptive ﬁrmware that was

programmed. The wireless modules (such as BLE,

ZigBee, Wi-Fi, or GPRS) can also be physically

removed from the main board, but in this case the

ﬁrmware is different when using BLE or ZigBee due

to incompatible I/O pins. The range of each wireless

technology results in 35 meters for BLE and 60

meters for ZigBee.

Non-volatile EEPROM memory can store up to

6500 samples. A sample consists of the measurement

of each sensor that the device has and the timestamp

in which it was measured. In order to access these

data, the device must be connected to the platform

trough an USB connection. The Online Platform has

been structured in four sections that include a central-

ized map, the visualization of the latest data from each

node (including the option to change sampling and

sending data rate), the retrieval of historical data and

a dynamic menu that allows physical connection to

each device via USB. This platform is exclusive only

for the researches with a username and password. The

Figure 5 shows data measured in two warehouses in a

museum in Lima, Peru. This Figure also shows how

can the user choose the sampling and sending data

rate. The Figure 6 shows historical data measured in-

side a laboratory. In this section, the user can choose

the environmental parameter from an speciﬁc device

in a speciﬁc network.

Figure 5: Online platform: latest data section.

Figure 6: Online platform: historical data section.

5 CONCLUSIONS

In this paper, we present the design and implementa-

tion of a modular WSN system for heritage conser-

vation. The system is battery powered and has long

autonomy depending on the sampling rate the user

choose for its application. The wide sensors set and

the modular hardware allow measuring different envi-

ronmental parameters corresponding to the most rele-

vant for each type of material. The use of Wi-Fi and

GPRS allows the use of this system in remote geo-

graphical locations and places with low technological

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174

resources. Finally, the easy-to-use online platform al-

lows the visualisation and handling of latest and his-

torical data of each node in network.

ACKNOWLEDGEMENTS

This work has been funded by the CONCYTEC –

World Bank Project ”Improvement and Expansion

of the Services of the National System of Science

Technology and Technological Innovation” 8682-PE,

through its executor entity PROCIENCIA [contract

number 035-2019].

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